Credit_Score.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-02-16T17:17:03.598654Z",
     "iopub.status.busy": "2024-02-16T17:17:03.597374Z",
     "iopub.status.idle": "2024-02-16T17:17:03.604927Z",
     "shell.execute_reply": "2024-02-16T17:17:03.603549Z",
     "shell.execute_reply.started": "2024-02-16T17:17:03.598611Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "from copy import deepcopy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Global Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-02-16T17:17:03.607266Z",
     "iopub.status.busy": "2024-02-16T17:17:03.606847Z",
     "iopub.status.idle": "2024-02-16T17:17:03.620829Z",
     "shell.execute_reply": "2024-02-16T17:17:03.619907Z",
     "shell.execute_reply.started": "2024-02-16T17:17:03.607228Z"
    }
   },
   "outputs": [],
   "source": [
    "epochs = 100\n",
    "r_epochs = 2000 # num epochs for regularization\n",
    "folds = 12\n",
    "a = 0.25 # alpha for regularization\n",
    "n_features = 87 # number of selected features after regularization\n",
    "degree = 2 # polynomial degree\n",
    "\n",
    "# local setup\n",
    "dataset_path = '../../Datasets/Kaggle/Credit_Score'\n",
    "output_path = dataset_path\n",
    "\n",
    "# kaggle kernel setup\n",
    "# dataset_path = '/kaggle/input/uwindsor-ai-club-can-credit-score-be-predicted'\n",
    "# output_path = '/kaggle/working'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_data(x, y):\n",
    "    plt.plot(x, y)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data(data):\n",
    "    df = pd.read_csv(data)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Train and Test Data\n",
    "\n",
    "kaggle link of the data : <br>\n",
    "https://www.kaggle.com/competitions/uwindsor-ai-club-can-credit-score-be-predicted/data <br>\n",
    "then download the <span style = \"color : red\">train.csv, test.csv and sample_submission.csv </span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read train and test data\n",
    "\n",
    "train_data = load_data(f'{dataset_path}/train.csv')\n",
    "test_data = load_data(f'{dataset_path}/test.csv')\n",
    "\n",
    "# sample_submission = load_data(f'{dataset_path}/sample_submission.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check Null values in Train and Test Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CUST_ID                0\n",
       "INCOME                 0\n",
       "SAVINGS                0\n",
       "DEBT                   0\n",
       "R_SAVINGS_INCOME       0\n",
       "                      ..\n",
       "CAT_MORTGAGE           0\n",
       "CAT_SAVINGS_ACCOUNT    0\n",
       "CAT_DEPENDENTS         0\n",
       "CREDIT_SCORE           0\n",
       "DEFAULT                0\n",
       "Length: 87, dtype: int64"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.isnull().sum()\n",
    "\n",
    "# train_data = train_data.sample(frac = 1, random_state = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Train\n",
      "\n",
      "Test\n"
     ]
    }
   ],
   "source": [
    "# prints out the columns and the num of null values if any null value is found\n",
    "print(f'\\nTrain')\n",
    "for i, val in enumerate(train_data.isnull().sum()):\n",
    "    if(val > 0):\n",
    "        print(f'col : {train_data.columns[i]}, val : {val}')\n",
    "print(f'\\nTest')\n",
    "for i, val in enumerate(test_data.isnull().sum()):\n",
    "    if(val > 0):\n",
    "        print(f'col : {test_data.columns[i]}, val : {val}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train and Test Splits\n",
    "\n",
    "- Keeping the train_data for train and val\n",
    "- Keeping the test_data for X_test only (y_test = CREDIT_SCORE column is not given, it should be predicted by us)\n",
    "- Dropping **CUST_ID** from X_train and X_test \n",
    "- train_data -> X_train, y_train (90% of the train.csv) (After feature selection)\n",
    "- test_data -> X_test (10% of the train.csv) (After feature selection) (y_test is not given)\n",
    "- Check the shapes to verify correct formatting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train.shape : (700, 85)\n",
      "y_train.shape : (700,)\n",
      "X_test.shape : (300, 85)\n"
     ]
    }
   ],
   "source": [
    "# dividing the data into two parts : predictors, targets\n",
    "X_train = train_data.drop(columns = ['CUST_ID', 'CREDIT_SCORE'], axis = 1)\n",
    "y_train = train_data['CREDIT_SCORE']\n",
    "\n",
    "X_test = test_data.drop('CUST_ID', axis = 1)\n",
    "\n",
    "print(f'X_train.shape : {X_train.shape}')\n",
    "print(f'y_train.shape : {y_train.shape}')\n",
    "print(f'X_test.shape : {X_test.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type(train_cols) : <class 'pandas.core.indexes.base.Index'>\n",
      "Number of train_cols : 85\n",
      "--------------------------------------------\n",
      "--------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# all the cols in the X_train\n",
    "train_cols = X_train.columns\n",
    "print(f'type(train_cols) : {type(train_cols)}')\n",
    "print(f'Number of train_cols : {len(train_cols)}')\n",
    "print(f'--------------------------------------------')\n",
    "print(f'--------------------------------------------')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inspect Data before Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sns.heatmap(train_data.isnull(), cmap = 'viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for col_name, col_type in train_data.dtypes.items():\n",
    "#     print(f'{col_name} -> {col_type}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CAT_GAMBLING\n",
       "No      439\n",
       "High    182\n",
       "Low      79\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data['CAT_GAMBLING'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing\n",
    "\n",
    "<br>\n",
    "\n",
    "- From this part we will be working **Only** with **X_train, X_test** (instead of train_data, test_data)\n",
    "- We have **CREDIT_SCORE** already separated\n",
    "- X_train and X_test do not have **CUST_ID** (Not a feature, so dropped it while forming X_train, X_test) \n",
    "- Convert the categorical col **CAT_GAMBLING** into 2 numerical dummy cols\n",
    "- Find columns which are highly correlated to one another and drop any one of them (pruning)\n",
    "- **CUST_ID** will be joined with y_pred after prediction "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CAT_GAMBLING\n",
       "No      181\n",
       "High     82\n",
       "Low      37\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test['CAT_GAMBLING'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train.cols : 67\n",
      "X_test.cols : 67\n",
      "\n",
      "X_train : (700, 67), y_train : (700,)\n",
      "X_train tail columns : Index(['No', 'Low', 'DEFAULT', 'CAT_DEPENDENTS'], dtype='object')\n",
      "\n",
      "X_test : (300, 67)\n",
      "X_test tail columns : Index(['No', 'Low', 'DEFAULT', 'CAT_DEPENDENTS'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "from itertools import combinations\n",
    "\n",
    "dummy_cols = pd.get_dummies(X_train['CAT_GAMBLING'], dtype = int, drop_first = True)\n",
    "dummy_cols_test = pd.get_dummies(X_test['CAT_GAMBLING'], dtype = int, drop_first = True)\n",
    "\n",
    "X_train = pd.concat([X_train.drop(columns = ['CAT_GAMBLING']), dummy_cols], axis = 1)\n",
    "X_test = pd.concat([X_test.drop(columns = ['CAT_GAMBLING']), dummy_cols_test], axis = 1)\n",
    "\n",
    "columns_to_drop = []\n",
    "\n",
    "for c1, c2 in combinations(X_train.columns, 2):\n",
    "    if np.abs(X_train[c1].corr(X_train[c2])) >= 0.88:\n",
    "#         print(f'c1 : {c1}, c2 : {c2}, corr = {X_train[c1].corr(X_train[c2])}')\n",
    "        columns_to_drop.append(c2)\n",
    "\n",
    "X_train.drop(columns = columns_to_drop, inplace = True, axis = 1)\n",
    "X_test.drop(columns = columns_to_drop, inplace = True, axis = 1)\n",
    "\n",
    "# Initial cols = 87\n",
    "# Removed CUST_ID, CREDIT_SCORE -> 85\n",
    "# Replaced CAT_GAMLING with 2 int cols -> 86\n",
    "print(f'X_train.cols : {len(X_train.columns)}')\n",
    "print(f'X_test.cols : {len(X_test.columns)}')\n",
    "\n",
    "# test whether the current data is in the correct shape\n",
    "print(f'\\nX_train : {X_train.shape}, y_train : {y_train.shape}')\n",
    "print(f'X_train tail columns : {X_train.columns[-1:-5:-1]}')\n",
    "print(f'\\nX_test : {X_test.shape}')\n",
    "print(f'X_test tail columns : {X_test.columns[-1:-5:-1]}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inspect after Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "# check the correlations of each feature target column pair\n",
    "\n",
    "# data = pd.concat([X_train, y_train], axis=1)\n",
    "\n",
    "# # Calculate the correlation matrix\n",
    "# correlation_matrix = data.corr()\n",
    "\n",
    "# # Define the threshold for low correlation\n",
    "# threshold = 0.2  # Adjust as needed\n",
    "\n",
    "# # Filter features with correlation below the threshold\n",
    "# low_corr_features = correlation_matrix[correlation_matrix['CREDIT_SCORE'].abs() < threshold].index\n",
    "\n",
    "# # Filter the correlation matrix to include only low correlation features\n",
    "# low_corr_matrix = correlation_matrix.loc[low_corr_features, low_corr_features]\n",
    "\n",
    "# # Plot the correlation matrix of low correlation features as a heatmap\n",
    "# plt.figure(figsize=(10, 8))\n",
    "# sns.heatmap(low_corr_matrix, annot = False, cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "# corr_threshold = 0.05\n",
    "\n",
    "# cols = []\n",
    "# # select features that are highly correlated with target \n",
    "# for col in X_train.columns:\n",
    "#     cr = X_train[col].corr(y_train)\n",
    "#     if(np.abs(cr) >= corr_threshold):\n",
    "#         cols.append(col)\n",
    "#         print(f'col : {col}, cr : {cr}')\n",
    "# print(f'total columns to include : {len(cols)}')\n",
    "\n",
    "# # include only the highly correlated cols in X_train and X_test\n",
    "# X_train = X_train[cols]\n",
    "# X_test = X_test[cols]\n",
    "\n",
    "# sns.pairplot(X_train)\n",
    "# print(f'X_train : {X_train.head()}')\n",
    "# print(f'X_test : {X_test.head()}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scale and Normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # normalize data\n",
    "# from mlxtend.preprocessing import minmax_scaling\n",
    "# from scipy import stats\n",
    "\n",
    "# # at first select the columns to apply the scaling and normalizing (except the binary cols)\n",
    "# bin_cols = X_train.columns[(X_train.eq(0) | X_train.eq(1)).all()]\n",
    "# non_bin_cols = X_train.columns.difference(bin_cols)\n",
    "\n",
    "# X_train, X_test = pd.concat([minmax_scaling(X_train, columns = non_bin_cols), X_train[bin_cols]], axis = 1), pd.concat([minmax_scaling(X_test, columns = non_bin_cols), X_test[bin_cols]], axis = 1)\n",
    "\n",
    "# # X_train[cols[2]], = stats.boxcox(X_train[cols[2]] + 0.5)\n",
    "\n",
    "# epsilon = 1e-10\n",
    "# for col in X_train.columns:\n",
    "#     if(col in non_bin_cols):\n",
    "#         X_train[col], _ = stats.boxcox(X_train[col] + epsilon)\n",
    "#         X_test[col], _ = stats.boxcox(X_test[col] + epsilon)\n",
    "\n",
    "# sns.pairplot(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # replace the zero values of the features with mean value\n",
    "# for col in X_train.columns:\n",
    "#     if(col != 'DEBT'):\n",
    "#         X_train[col].replace(0, 1, inplace = True)\n",
    "#         X_test[col].replace(0, 1, inplace = True)\n",
    "        \n",
    "\n",
    "# # inspect distributions of the features\n",
    "# X_train = pd.concat([np.log(X_train.iloc[:,:-1]), X_train.iloc[:,-1]], axis = 1)\n",
    "# X_test = pd.concat([np.log(X_test.iloc[:,:-1]), X_test.iloc[:,-1]], axis = 1)\n",
    "\n",
    "# sns.pairplot(X_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ...........................................................\n",
    "# Baselines\n",
    "### ..........................................................."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-02-16T17:10:54.895035Z",
     "iopub.status.busy": "2024-02-16T17:10:54.894587Z",
     "iopub.status.idle": "2024-02-16T17:10:55.481160Z",
     "shell.execute_reply": "2024-02-16T17:10:55.479583Z",
     "shell.execute_reply.started": "2024-02-16T17:10:54.895001Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LR mean rmse = 28.239422809192064\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "lr = LinearRegression()\n",
    "nmse = cross_val_score(lr, X_train, y_train, scoring = 'neg_mean_squared_error', cv = folds)\n",
    "mean_rmse = np.mean(np.sqrt(-nmse))\n",
    "\n",
    "print(f'LR mean rmse = {mean_rmse}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ridge Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-02-16T17:11:13.774712Z",
     "iopub.status.busy": "2024-02-16T17:11:13.773797Z",
     "iopub.status.idle": "2024-02-16T17:11:21.971229Z",
     "shell.execute_reply": "2024-02-16T17:11:21.969468Z",
     "shell.execute_reply.started": "2024-02-16T17:11:13.774671Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RR best alpha = {'ridge__alpha': 20, 'ridge__max_iter': 100}\n",
      "RR rmse = 28.165729554688834\n"
     ]
    }
   ],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "ridge = Ridge()\n",
    "params = {'ridge__alpha' : [1e-2, 1, 5, 10, 20, 30, 35, 40, 45, 50, 100], \\\n",
    "          'ridge__max_iter' : [100, 500, 1000, 2500]}\n",
    "pipeline = Pipeline([\n",
    "    ('scaler', StandardScaler()),\n",
    "    ('ridge', ridge)\n",
    "])\n",
    "rr = GridSearchCV(pipeline, params, scoring = 'neg_mean_squared_error', cv = folds)\n",
    "rr.fit(X_train, y_train)\n",
    "\n",
    "# best params\n",
    "a = rr.best_params_\n",
    "nmse = rr.best_score_\n",
    "rmse = np.sqrt(-nmse)\n",
    "\n",
    "print(f'RR best alpha = {a}')\n",
    "print(f'RR rmse = {rmse}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lasso Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "_kg_hide-output": false,
    "execution": {
     "iopub.execute_input": "2024-02-16T17:13:36.198200Z",
     "iopub.status.busy": "2024-02-16T17:13:36.197645Z",
     "iopub.status.idle": "2024-02-16T17:13:45.089387Z",
     "shell.execute_reply": "2024-02-16T17:13:45.087607Z",
     "shell.execute_reply.started": "2024-02-16T17:13:36.198164Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.152e+05, tolerance: 2.575e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 2.513e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 2.658e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 2.673e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.033e+05, tolerance: 2.576e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.028e+05, tolerance: 2.627e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 2.619e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 2.612e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 2.601e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.010e+05, tolerance: 2.714e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 2.695e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 2.583e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.152e+05, tolerance: 5.151e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 5.025e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 5.316e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 5.345e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.033e+05, tolerance: 5.152e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.028e+05, tolerance: 5.255e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 5.238e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 5.223e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 5.201e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.010e+05, tolerance: 5.427e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 5.389e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 5.166e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.152e+05, tolerance: 7.726e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 7.538e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 7.973e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 8.018e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.033e+05, tolerance: 7.728e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.028e+05, tolerance: 7.882e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 7.858e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 7.835e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 7.802e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.010e+05, tolerance: 8.141e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 8.084e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 7.749e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.152e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 1.256e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 1.329e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 1.336e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.033e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.028e+05, tolerance: 1.314e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 1.310e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 1.306e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 1.300e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.010e+05, tolerance: 1.357e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 1.347e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 1.292e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.152e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 1.256e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 1.329e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 1.336e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.033e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.028e+05, tolerance: 1.314e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 1.306e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.010e+05, tolerance: 1.357e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 1.347e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 1.292e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.151e+05, tolerance: 2.575e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 2.513e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 2.658e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 2.673e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.032e+05, tolerance: 2.576e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.026e+05, tolerance: 2.627e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 2.619e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 2.612e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.042e+05, tolerance: 2.601e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.007e+05, tolerance: 2.714e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 2.695e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 2.583e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.151e+05, tolerance: 5.151e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 5.025e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 5.316e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 5.345e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.032e+05, tolerance: 5.152e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.026e+05, tolerance: 5.255e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 5.238e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 5.223e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.042e+05, tolerance: 5.201e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.007e+05, tolerance: 5.427e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 5.389e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 5.166e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.151e+05, tolerance: 7.726e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 7.538e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 7.973e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 8.018e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.032e+05, tolerance: 7.728e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.026e+05, tolerance: 7.882e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 7.858e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 7.835e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.042e+05, tolerance: 7.802e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.007e+05, tolerance: 8.141e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 8.084e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 7.749e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.151e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 1.256e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 1.329e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 1.336e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.032e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.026e+05, tolerance: 1.314e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 1.310e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 1.306e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.042e+05, tolerance: 1.300e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.007e+05, tolerance: 1.357e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 1.347e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 1.292e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.151e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+05, tolerance: 1.256e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+05, tolerance: 1.329e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.056e+05, tolerance: 1.336e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.032e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.026e+05, tolerance: 1.314e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.902e+05, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.088e+05, tolerance: 1.306e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.042e+05, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.007e+05, tolerance: 1.357e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+05, tolerance: 1.347e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 1.292e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 2.575e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.061e+05, tolerance: 2.513e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.053e+05, tolerance: 2.658e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.439e+05, tolerance: 2.673e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.601e+05, tolerance: 2.576e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.846e+04, tolerance: 2.627e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.754e+05, tolerance: 2.619e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.038e+05, tolerance: 2.612e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.922e+05, tolerance: 2.601e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.188e+05, tolerance: 2.714e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.797e+05, tolerance: 2.695e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.909e+05, tolerance: 2.583e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 5.151e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.061e+05, tolerance: 5.025e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.053e+05, tolerance: 5.316e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.439e+05, tolerance: 5.345e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.601e+05, tolerance: 5.152e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.846e+04, tolerance: 5.255e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.754e+05, tolerance: 5.238e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.038e+05, tolerance: 5.223e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.922e+05, tolerance: 5.201e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.188e+05, tolerance: 5.427e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.797e+05, tolerance: 5.389e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.909e+05, tolerance: 5.166e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 7.726e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.061e+05, tolerance: 7.538e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.053e+05, tolerance: 7.973e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.439e+05, tolerance: 8.018e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.601e+05, tolerance: 7.728e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.846e+04, tolerance: 7.882e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.754e+05, tolerance: 7.858e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.038e+05, tolerance: 7.835e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.922e+05, tolerance: 7.802e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.188e+05, tolerance: 8.141e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.797e+05, tolerance: 8.084e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.909e+05, tolerance: 7.749e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.061e+05, tolerance: 1.256e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.053e+05, tolerance: 1.329e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.439e+05, tolerance: 1.336e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.601e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.754e+05, tolerance: 1.310e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.038e+05, tolerance: 1.306e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.922e+05, tolerance: 1.300e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.797e+05, tolerance: 1.347e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.909e+05, tolerance: 1.292e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.061e+05, tolerance: 1.256e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.053e+05, tolerance: 1.329e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.439e+05, tolerance: 1.336e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.601e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.846e+04, tolerance: 1.314e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.754e+05, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.038e+05, tolerance: 1.306e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.922e+05, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.188e+05, tolerance: 1.357e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.797e+05, tolerance: 1.347e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.909e+05, tolerance: 1.292e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.141e+05, tolerance: 2.575e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 2.513e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 2.658e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.046e+05, tolerance: 2.673e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.025e+05, tolerance: 2.576e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 2.627e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 2.619e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 2.612e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.037e+05, tolerance: 2.601e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.964e+05, tolerance: 2.714e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+05, tolerance: 2.695e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.036e+05, tolerance: 2.583e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.141e+05, tolerance: 5.151e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 5.025e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 5.316e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.046e+05, tolerance: 5.345e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.025e+05, tolerance: 5.152e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 5.255e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 5.238e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 5.223e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.037e+05, tolerance: 5.201e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.964e+05, tolerance: 5.427e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+05, tolerance: 5.389e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.036e+05, tolerance: 5.166e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.141e+05, tolerance: 7.726e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 7.538e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 7.973e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.046e+05, tolerance: 8.018e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.025e+05, tolerance: 7.728e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 7.882e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 7.858e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 7.835e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.037e+05, tolerance: 7.802e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.964e+05, tolerance: 8.141e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+05, tolerance: 8.084e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.036e+05, tolerance: 7.749e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.141e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 1.256e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 1.329e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.046e+05, tolerance: 1.336e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.025e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 1.314e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 1.310e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 1.306e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.037e+05, tolerance: 1.300e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.964e+05, tolerance: 1.357e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+05, tolerance: 1.347e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.036e+05, tolerance: 1.292e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.141e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 1.256e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.049e+05, tolerance: 1.329e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.046e+05, tolerance: 1.336e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.025e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 1.314e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.898e+05, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.080e+05, tolerance: 1.306e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.037e+05, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.964e+05, tolerance: 1.357e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+05, tolerance: 1.347e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.036e+05, tolerance: 1.292e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+05, tolerance: 2.575e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+05, tolerance: 2.513e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 2.658e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.963e+05, tolerance: 2.673e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.962e+05, tolerance: 2.576e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.859e+05, tolerance: 2.627e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+05, tolerance: 2.619e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.048e+05, tolerance: 2.612e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.004e+05, tolerance: 2.601e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+05, tolerance: 2.714e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 2.695e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.971e+05, tolerance: 2.583e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+05, tolerance: 5.151e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+05, tolerance: 5.025e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 5.316e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.963e+05, tolerance: 5.345e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.962e+05, tolerance: 5.152e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.859e+05, tolerance: 5.255e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+05, tolerance: 5.238e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.048e+05, tolerance: 5.223e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.004e+05, tolerance: 5.201e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+05, tolerance: 5.427e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 5.389e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.971e+05, tolerance: 5.166e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+05, tolerance: 7.726e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+05, tolerance: 7.538e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 7.973e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.963e+05, tolerance: 8.018e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.962e+05, tolerance: 7.728e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.859e+05, tolerance: 7.882e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+05, tolerance: 7.858e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.048e+05, tolerance: 7.835e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.004e+05, tolerance: 7.802e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+05, tolerance: 8.141e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 8.084e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.971e+05, tolerance: 7.749e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+05, tolerance: 1.256e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 1.329e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.963e+05, tolerance: 1.336e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.962e+05, tolerance: 1.288e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.859e+05, tolerance: 1.314e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+05, tolerance: 1.310e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.048e+05, tolerance: 1.306e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.004e+05, tolerance: 1.300e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+05, tolerance: 1.357e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 1.347e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.971e+05, tolerance: 1.292e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+05, tolerance: 1.256e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+05, tolerance: 1.329e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.963e+05, tolerance: 1.336e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.962e+05, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.859e+05, tolerance: 1.314e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+05, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.048e+05, tolerance: 1.306e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.004e+05, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+05, tolerance: 1.357e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.011e+05, tolerance: 1.347e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.971e+05, tolerance: 1.292e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.058e+04, tolerance: 2.513e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.953e+05, tolerance: 2.658e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.218e+04, tolerance: 2.612e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.058e+04, tolerance: 5.025e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.953e+05, tolerance: 5.316e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.058e+04, tolerance: 7.538e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.953e+05, tolerance: 7.973e+04\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.953e+05, tolerance: 1.329e+05\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 3.852e+03, tolerance: 1.288e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.058e+04, tolerance: 1.256e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.953e+05, tolerance: 1.329e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.163e+03, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.218e+04, tolerance: 1.306e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.211e+04, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.531e+03, tolerance: 1.347e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.396e+03, tolerance: 1.292e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.822e+03, tolerance: 1.310e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "C:\\Users\\Jamil88\\.conda\\envs\\nlp\\Lib\\site-packages\\sklearn\\linear_model\\_coordinate_descent.py:678: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 4.783e+03, tolerance: 1.300e+03\n",
      "  model = cd_fast.enet_coordinate_descent(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lasso_regressor best alpha = {'lasso__alpha': 1, 'lasso__max_iter': 500, 'lasso__tol': 0.01}\n",
      "lasso_regressor rmse = 27.531706402729764\n"
     ]
    }
   ],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "lasso_regressor = Lasso()\n",
    "params = {'lasso__alpha' : [1e-7, 1e-5, 1e-2, 1, 5, 10, 20, 30, 35, 40], \\\n",
    "          'lasso__max_iter' : [500, 1000, 2500], \\\n",
    "         'lasso__tol' : [0.01, 0.02, 0.03, 0.05, 0.0005]}\n",
    "#          'lasso__tol' : [0.05]}\n",
    "pipeline = Pipeline([\n",
    "    ('scaler', StandardScaler()),\n",
    "    ('lasso', lasso_regressor)\n",
    "])\n",
    "lasso_regressor = GridSearchCV(pipeline, params, scoring = 'neg_mean_squared_error', cv = folds)\n",
    "lasso_regressor.fit(X_train, y_train)\n",
    "\n",
    "# best params\n",
    "a = lasso_regressor.best_params_\n",
    "nmse = lasso_regressor.best_score_\n",
    "rmse = np.sqrt(-nmse)\n",
    "\n",
    "print(f'lasso_regressor best alpha = {a}')\n",
    "print(f'lasso_regressor rmse = {rmse}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### XGBoost\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from xgboost import XGBRegressor\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from scipy.stats import uniform, randint\n",
    "\n",
    "# Create an XGBoost regressor model\n",
    "xgb = XGBRegressor()\n",
    "\n",
    "# Best parameters: {'n_estimators': 250, 'min_child_weight': 3, 'max_depth': 2, 'learning_rate': 0.05, 'lambda': 20, 'booster': 'gbtree'}\n",
    "\n",
    "# pass 2\n",
    "param_dist = {\n",
    "    'learning_rate': [0.01, 0.05, 0.1],\n",
    "    'max_depth': [2, 3, 5, 10],\n",
    "    'booster' : ['gbtree'],\n",
    "    'min_child_weight': [1, 2, 3, 4, 5],\n",
    "    'lambda' : [0.1, 0.5, 1, 5, 10, 20, 30],\n",
    "    'n_estimators': [50, 100, 250, 500, 1000, 1500]\n",
    "}\n",
    "\n",
    "# Perform randomized search with cross-validation\n",
    "random_search = RandomizedSearchCV(xgb, param_distributions=param_dist, n_iter=100, scoring='neg_mean_squared_error', cv=folds)\n",
    "random_search.fit(X_train, y_train)\n",
    "\n",
    "# Get the best parameters and RMSE score\n",
    "best_params = random_search.best_params_\n",
    "best_rmse = np.sqrt(-random_search.best_score_)\n",
    "\n",
    "print(\"Best parameters:\", best_params)\n",
    "print(\"Best RMSE:\", best_rmse)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Experimental Model Section\n",
    "\n",
    "To test the model drafts here (The data preprocessing should be done beforehand)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_bk, y_train_bk, X_test_bk = X_train, y_train, X_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "................... Fold : 1 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "012f7e4a96d640d6a83d8abb8e973b3e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 1 : 35.87628788247974\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 2 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0dfa21a5a5e94961b14164b66b22686a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 2 : 47.970012198377646\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 3 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b1edd197602944878d9f964b5871d45f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 3 : 37.84707226333696\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 4 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b9291befac1c4a50a16c4667855410b6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 4 : 46.80984012803825\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 5 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6d035ef616f94c498fed19e0fa3d6eb4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 5 : 42.90689297588151\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 6 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f4142a89c05f4c3995f7c466ffbbd15a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 6 : 47.88314582707443\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 7 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "422ba4c2c30349f898f5d28e9fa2be59",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 7 : 40.96834924241441\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 8 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a3cde4bc28774cc1885355ea3e09c67b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 8 : 50.58455174260221\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 9 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3bab23b91f934ffd99b985a7878c7faa",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 9 : 49.229691244207494\n",
      "-------------------------------------\n",
      "\n",
      "................... Fold : 10 ...............\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d4a8018462d4efd99453d9bd3e60338",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "val_loss at fold 10 : 43.21770775587103\n",
      "-------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average validation loss across 10 folds: 44.5804\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.utils.data import DataLoader, TensorDataset\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.preprocessing import StandardScaler, Normalizer\n",
    "from tqdm.notebook import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "class NeuralNet(nn.Module):\n",
    "    def __init__(self, input_size):\n",
    "        super(NeuralNet, self).__init__()\n",
    "        self.fc1 = nn.Linear(input_size, 64)\n",
    "        self.relu = nn.ReLU()\n",
    "        self.dropout1 = nn.Dropout(0.1)  # Add dropout layer with dropout probability of 0.5\n",
    "        self.fc2 = nn.Linear(64, 64)\n",
    "        self.dropout2 = nn.Dropout(0.1)  # Add dropout layer with dropout probability of 0.5\n",
    "        self.fc3 = nn.Linear(64, 32)\n",
    "        self.dropout3 = nn.Dropout(0.1)\n",
    "        self.fc4 = nn.Linear(32, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.relu(self.fc1(x))\n",
    "        x = self.dropout1(x)\n",
    "        x = self.relu(self.fc2(x))\n",
    "        x = self.dropout2(x)\n",
    "        x = self.fc3(x)\n",
    "        x = self.dropout3(x)\n",
    "        x = self.fc4(x)\n",
    "        return x\n",
    "\n",
    "# Function to train and evaluate the model\n",
    "def train_and_evaluate_model(X_train, y_train, train_index, val_index):\n",
    "    # Convert data to PyTorch tensors\n",
    "    X_train_tensor = torch.tensor(X_train[train_index], dtype=torch.float32)\n",
    "    y_train_tensor = torch.tensor(y_train.values[train_index], dtype=torch.float32).view(-1, 1)  # Reshape y to column vector\n",
    "    X_val_tensor = torch.tensor(X_train[val_index], dtype=torch.float32)\n",
    "    y_val_tensor = torch.tensor(y_train.values[val_index], dtype=torch.float32).view(-1, 1)  # Reshape y to column vector\n",
    "\n",
    "    # Instantiate the model\n",
    "    input_size = X_train.shape[1]\n",
    "    model = NeuralNet(input_size)\n",
    "\n",
    "    # Define loss function and optimizer\n",
    "    criterion = nn.MSELoss()\n",
    "    optimizer = optim.Adam(model.parameters(), lr=0.001)\n",
    "\n",
    "    # Convert data to DataLoader\n",
    "    train_dataset = TensorDataset(X_train_tensor, y_train_tensor)\n",
    "    train_loader = DataLoader(train_dataset, batch_size=32, shuffle=True)\n",
    "\n",
    "    # Training the model\n",
    "    num_epochs = 100\n",
    "    losses = [] # collecting all the average losses over epochs\n",
    "    \n",
    "    for epoch in tqdm(range(num_epochs)):\n",
    "        total_loss = 0\n",
    "        total_examples = 0\n",
    "        for inputs, targets in train_loader:\n",
    "            optimizer.zero_grad()\n",
    "            outputs = model(inputs)\n",
    "            loss = criterion(outputs, targets)\n",
    "            total_loss += loss\n",
    "            total_examples += len(targets)\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "#         # the average loss over all the batches\n",
    "#         print(f'epoch : {epoch}, loss : {total_loss / total_examples}')\n",
    "        losses.append(total_loss.detach().numpy() / total_examples)\n",
    "        \n",
    "#     plot_pts = [list(np.arange(num_epochs)), losses]\n",
    "    # plot training losses\n",
    "#     plot_data(plot_pts[0], plot_pts[1])\n",
    "    \n",
    "    # Evaluation\n",
    "    with torch.no_grad():\n",
    "        model.eval()\n",
    "        outputs = model(X_val_tensor)\n",
    "        val_loss = criterion(outputs, y_val_tensor)\n",
    "        return val_loss.item()\n",
    "\n",
    "# Assume your data is X_train and y_train\n",
    "\n",
    "# Normalize the data\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X_train)\n",
    "# X_scaled = X_train\n",
    "\n",
    "# Define 10-fold cross-validation\n",
    "kf = KFold(n_splits=10, shuffle=False)\n",
    "\n",
    "val_losses = []\n",
    "f = 1\n",
    "# Perform 10-fold cross-validation\n",
    "for train_index, val_index in kf.split(X_scaled):\n",
    "    print(f'................... Fold : {f} ...............\\n')\n",
    "    val_loss = train_and_evaluate_model(X_scaled, y_train, train_index, val_index)\n",
    "    print(f'\\nval_loss at fold {f} : {np.sqrt(val_loss)}')\n",
    "    print(f'-------------------------------------\\n')\n",
    "    val_losses.append(val_loss)\n",
    "    f += 1\n",
    "\n",
    "plot_pts = [range(f - 1), val_losses]\n",
    "plot_data(plot_pts[0], plot_pts[1])\n",
    "    \n",
    "# Compute average validation loss\n",
    "avg_val_loss = np.sqrt(np.mean(val_losses))\n",
    "print(f'Average validation loss across 10 folds: {avg_val_loss:.4f}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Baseline Results\n",
    "\n",
    "| ID | Model | Degree | Epochs | Regularization | Reg Epochs, Tol, Correlation Threshold, Selection | Lambda | N_features | Folds | RMSE |\n",
    "| --- | ---- | -------- | ----- | -------------- | ----- | ------ | ----- | ---- | ---- |\n",
    "| 1 | lr | 1 | None | None | None | 0 | All | 0 | **24.86964904316159** |\n",
    "| 2 | lr | 1 | None | L2 | X | 20 | X | 10 | 28.506133250715063 |\n",
    "| 3 | lr | 1 | None | None | None | 0 | 86 | 10 | **29.18143127944806** |\n",
    "| 4 | lr | 1 | None | L1 | 1000 | 1 | X | 10 | 27.67585141705469 | \n",
    "| 5 | lr | 1 | None | L1 | 10000, 0.01 | 1 | X | 10 | 27.666622998342643 |\n",
    "| 6 | lr | 2 | None | L2 | 2000 | 100 | X | 10 | 44.09927407811474 | \n",
    "| 7 | lr | 1 | None | L2 | 2000 | 20 | 68 (Correlation drop off) | 10 | 28.353964603124588 |\n",
    "| 8 | lr | 1 | None | L1 | 2000 | 1 | 68 | 10 | 27.617890371610304 |\n",
    "| 9 | lr | 1 | None | L1 | 2000, 0.01, 0.9 | 1 | 68 | 12 | 27.531726534989563 |\n",
    "| 10 | lr | 1 | None | L1 | 2000, 0.01, 0.89 | 1 | 68 | 12 | 27.531706402729764 |\n",
    "| 11 | lr | 1 | None | L1 | 2500, 0.03, 0.89, random | 1 | 67 | 12 | **27.369576649451645** |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Build the Best Model\n",
    "\n",
    "Select the best model from the grid_search or random_search's best_params and then create the model before prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-02-16T17:15:27.415463Z",
     "iopub.status.busy": "2024-02-16T17:15:27.414997Z",
     "iopub.status.idle": "2024-02-16T17:15:27.436237Z",
     "shell.execute_reply": "2024-02-16T17:15:27.433960Z",
     "shell.execute_reply.started": "2024-02-16T17:15:27.415432Z"
    }
   },
   "outputs": [],
   "source": [
    "print(f'X_test.shape : {X_test.shape}')\n",
    "\n",
    "# predict\n",
    "# y_test = rr.predict(X_test)\n",
    "y_test = lasso_regressor.predict(X_test)\n",
    "\n",
    "test_data_output = pd.DataFrame({'CUST_ID' : test_data['CUST_ID'], 'CREDIT_SCORE' : y_test})\n",
    "\n",
    "print(f'test_data_output.columns : {test_data_output.columns}')\n",
    "print(f'test_data_output.shape : {test_data_output.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Save Output for Submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-02-16T17:15:43.054492Z",
     "iopub.status.busy": "2024-02-16T17:15:43.054003Z",
     "iopub.status.idle": "2024-02-16T17:15:43.064230Z",
     "shell.execute_reply": "2024-02-16T17:15:43.063017Z",
     "shell.execute_reply.started": "2024-02-16T17:15:43.054458Z"
    }
   },
   "outputs": [],
   "source": [
    "test_data_output.to_csv(f'{output_path}/submission_id10.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "databundleVersionId": 7626890,
     "sourceId": 68740,
     "sourceType": "competition"
    }
   ],
   "dockerImageVersionId": 30646,
   "isGpuEnabled": false,
   "isInternetEnabled": false,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "Python [conda env:.conda-nlp]",
   "language": "python",
   "name": "conda-env-.conda-nlp-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}