random_forest_ml_tabular_data.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"random_forest_ml_tabular_data.ipynb","provenance":[],"mount_file_id":"16r-6xlnNiti6PpCchwNE_H88wFzmUV24","authorship_tag":"ABX9TyPCBEnfd3w56+1C1yzkFP6a"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"id":"ucWIdkeONPqD","executionInfo":{"status":"ok","timestamp":1654633672072,"user_tz":-120,"elapsed":882,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}}},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import re"]},{"cell_type":"markdown","source":["Importing data in pandas"],"metadata":{"id":"wPjKM33eNbGS"}},{"cell_type":"code","source":["from pandas.io.pytables import DataCol\n","data = pd.read_excel('/content/drive/MyDrive/zebra classification /Zebras.Assumption.data_Bing_413 .xlsx',\n","              sheet_name='Assumptions.all')\n","\n","data  "],"metadata":{"id":"wJLibhtANd8i","executionInfo":{"status":"ok","timestamp":1654633681270,"user_tz":-120,"elapsed":848,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}},"colab":{"base_uri":"https://localhost:8080/","height":406},"outputId":"7a353f29-4009-48a6-a395-45c05b525568"},"execution_count":2,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                      file      q25      q50      q75    fpeak  duration  \\\n","0    05011.squeal.trim.wav    1.024   22.542  144.346  509.753     0.234   \n","1    05073.squeal.trim.wav    4.626  391.921  635.612  537.097     0.155   \n","2    05074.squeal.trim.wav    9.773  558.276  806.924  769.535     0.087   \n","3    18023.squeal.trim.wav  378.288  439.051  489.999  442.747     0.165   \n","4    19002.squeal.trim.wav  414.270  485.271  627.478  449.798     0.138   \n","..                     ...      ...      ...      ...      ...       ...   \n","408   83033.snort.trim.wav    2.413   33.731  162.388  689.083     0.303   \n","409   83035.snort.trim.wav   12.324  106.265  286.088  181.432     0.169   \n","410   83051.snort.trim.wav    1.511   47.826  302.461  197.067     0.549   \n","411   83053.snort.trim.wav    4.978   70.706  211.919   94.333     0.669   \n","412   83054.snort.trim.wav    2.142   33.163  142.663  872.093     0.514   \n","\n","      am.var  am.rate  am.extent  harmonicity  \n","0    203.701   25.684      7.931        10.16  \n","1    204.375   16.133     12.668        20.27  \n","2    243.896    5.745     42.452        17.58  \n","3    245.843    9.098     27.022        13.51  \n","4    225.379   18.142     12.423        13.93  \n","..       ...      ...        ...          ...  \n","408  413.913   34.701     11.928         6.15  \n","409  386.167   29.581     13.054         8.15  \n","410  393.041   25.510     15.407         4.52  \n","411  477.292   29.899     15.963         7.78  \n","412  448.085   30.173     14.850        11.90  \n","\n","[413 rows x 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<td>144.346</td>\n","      <td>509.753</td>\n","      <td>0.234</td>\n","      <td>203.701</td>\n","      <td>25.684</td>\n","      <td>7.931</td>\n","      <td>10.16</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>05073.squeal.trim.wav</td>\n","      <td>4.626</td>\n","      <td>391.921</td>\n","      <td>635.612</td>\n","      <td>537.097</td>\n","      <td>0.155</td>\n","      <td>204.375</td>\n","      <td>16.133</td>\n","      <td>12.668</td>\n","      <td>20.27</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>05074.squeal.trim.wav</td>\n","      <td>9.773</td>\n","      <td>558.276</td>\n","      <td>806.924</td>\n","      <td>769.535</td>\n","      <td>0.087</td>\n","      <td>243.896</td>\n","      <td>5.745</td>\n","      <td>42.452</td>\n","      <td>17.58</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>18023.squeal.trim.wav</td>\n","      <td>378.288</td>\n","      <td>439.051</td>\n","      <td>489.999</td>\n","      <td>442.747</td>\n","      <td>0.165</td>\n","      <td>245.843</td>\n","      <td>9.098</td>\n","      <td>27.022</td>\n","      <td>13.51</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>19002.squeal.trim.wav</td>\n","      <td>414.270</td>\n","      <td>485.271</td>\n","      <td>627.478</td>\n","      <td>449.798</td>\n","      <td>0.138</td>\n","      <td>225.379</td>\n","      <td>18.142</td>\n","      <td>12.423</td>\n","      <td>13.93</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>408</th>\n","      <td>83033.snort.trim.wav</td>\n","      <td>2.413</td>\n","      <td>33.731</td>\n","      <td>162.388</td>\n","      <td>689.083</td>\n","      <td>0.303</td>\n","      <td>413.913</td>\n","      <td>34.701</td>\n","      <td>11.928</td>\n","      <td>6.15</td>\n","    </tr>\n","    <tr>\n","      <th>409</th>\n","      <td>83035.snort.trim.wav</td>\n","      <td>12.324</td>\n","      <td>106.265</td>\n","      <td>286.088</td>\n","      <td>181.432</td>\n","      <td>0.169</td>\n","      <td>386.167</td>\n","      <td>29.581</td>\n","      <td>13.054</td>\n","      <td>8.15</td>\n","    </tr>\n","    <tr>\n","      <th>410</th>\n","      <td>83051.snort.trim.wav</td>\n","      <td>1.511</td>\n","      <td>47.826</td>\n","      <td>302.461</td>\n","      <td>197.067</td>\n","      <td>0.549</td>\n","      <td>393.041</td>\n","      <td>25.510</td>\n","      <td>15.407</td>\n","      <td>4.52</td>\n","    </tr>\n","    <tr>\n","      <th>411</th>\n","      <td>83053.snort.trim.wav</td>\n","      <td>4.978</td>\n","      <td>70.706</td>\n","      <td>211.919</td>\n","      <td>94.333</td>\n","      <td>0.669</td>\n","      <td>477.292</td>\n","      <td>29.899</td>\n","      <td>15.963</td>\n","      <td>7.78</td>\n","    </tr>\n","    <tr>\n","      <th>412</th>\n","      <td>83054.snort.trim.wav</td>\n","      <td>2.142</td>\n","      <td>33.163</td>\n","      <td>142.663</td>\n","      <td>872.093</td>\n","      <td>0.514</td>\n","      <td>448.085</td>\n","      <td>30.173</td>\n","      <td>14.850</td>\n","      <td>11.90</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>413 rows × 10 columns</p>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-31d32ac8-6f24-4bfa-bb1f-333d805e3415')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 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Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "]},"metadata":{},"execution_count":2}]},{"cell_type":"markdown","source":["Creating the labels from the 'file' column"],"metadata":{"id":"gExyf5BOcLpQ"}},{"cell_type":"code","source":["labels = []\n","for i in data['file']:\n","  y = re.findall('whinnie|snort|softsnort|squeal', i)\n","  labels.append(y)\n"],"metadata":{"id":"z-lzSeXOcARJ","executionInfo":{"status":"ok","timestamp":1654633685696,"user_tz":-120,"elapsed":633,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}}},"execution_count":3,"outputs":[]},{"cell_type":"code","source":["#clever way of doing that above\n","# [re.findall('whinnie|snort|softsnort|squeal', i) for i in data['file']]"],"metadata":{"id":"t_wvOFcdoThn"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Adding the labels to the dataset"],"metadata":{"id":"bAC7NgrPnj5V"}},{"cell_type":"code","source":["data[['labels']] = labels"],"metadata":{"id":"jK5_rbM8nDVD","executionInfo":{"status":"ok","timestamp":1654633693631,"user_tz":-120,"elapsed":588,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}}},"execution_count":4,"outputs":[]},{"cell_type":"markdown","source":["Removing the file column"],"metadata":{"id":"IHEJK9WansS2"}},{"cell_type":"code","source":["data.drop(\"file\", axis=1, inplace = True)\n","data"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":406},"id":"p5mRxcotnVZE","executionInfo":{"status":"ok","timestamp":1654633695821,"user_tz":-120,"elapsed":253,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}},"outputId":"dbfd97c8-d1d0-4856-d45a-7487cc48bb8e"},"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["         q25      q50      q75    fpeak  duration   am.var  am.rate  \\\n","0      1.024   22.542  144.346  509.753     0.234  203.701   25.684   \n","1      4.626  391.921  635.612  537.097     0.155  204.375   16.133   \n","2      9.773  558.276  806.924  769.535     0.087  243.896    5.745   \n","3    378.288  439.051  489.999  442.747     0.165  245.843    9.098   \n","4    414.270  485.271  627.478  449.798     0.138  225.379   18.142   \n","..       ...      ...      ...      ...       ...      ...      ...   \n","408    2.413   33.731  162.388  689.083     0.303  413.913   34.701   \n","409   12.324  106.265  286.088  181.432     0.169  386.167   29.581   \n","410    1.511   47.826  302.461  197.067     0.549  393.041   25.510   \n","411    4.978   70.706  211.919   94.333     0.669  477.292   29.899   \n","412    2.142   33.163  142.663  872.093     0.514  448.085   30.173   \n","\n","     am.extent  harmonicity  labels  \n","0        7.931        10.16  squeal  \n","1       12.668        20.27  squeal  \n","2       42.452        17.58  squeal  \n","3       27.022        13.51  squeal  \n","4       12.423        13.93  squeal  \n","..         ...          ...     ...  \n","408     11.928         6.15   snort  \n","409     13.054         8.15   snort  \n","410     15.407         4.52   snort  \n","411     15.963         7.78   snort  \n","412     14.850        11.90   snort  \n","\n","[413 rows x 10 columns]"],"text/html":["\n","  <div id=\"df-f95f5a6a-65b0-49b9-9c26-3ea9fba10ad3\">\n","    <div class=\"colab-df-container\">\n","      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<td>squeal</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>4.626</td>\n","      <td>391.921</td>\n","      <td>635.612</td>\n","      <td>537.097</td>\n","      <td>0.155</td>\n","      <td>204.375</td>\n","      <td>16.133</td>\n","      <td>12.668</td>\n","      <td>20.27</td>\n","      <td>squeal</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>9.773</td>\n","      <td>558.276</td>\n","      <td>806.924</td>\n","      <td>769.535</td>\n","      <td>0.087</td>\n","      <td>243.896</td>\n","      <td>5.745</td>\n","      <td>42.452</td>\n","      <td>17.58</td>\n","      <td>squeal</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>378.288</td>\n","      <td>439.051</td>\n","      <td>489.999</td>\n","      <td>442.747</td>\n","      <td>0.165</td>\n","      <td>245.843</td>\n","      <td>9.098</td>\n","      <td>27.022</td>\n","      <td>13.51</td>\n","      <td>squeal</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>414.270</td>\n","      <td>485.271</td>\n","      <td>627.478</td>\n","      <td>449.798</td>\n","      <td>0.138</td>\n","      <td>225.379</td>\n","      <td>18.142</td>\n","      <td>12.423</td>\n","      <td>13.93</td>\n","      <td>squeal</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>408</th>\n","      <td>2.413</td>\n","      <td>33.731</td>\n","      <td>162.388</td>\n","      <td>689.083</td>\n","      <td>0.303</td>\n","      <td>413.913</td>\n","      <td>34.701</td>\n","      <td>11.928</td>\n","      <td>6.15</td>\n","      <td>snort</td>\n","    </tr>\n","    <tr>\n","      <th>409</th>\n","      <td>12.324</td>\n","      <td>106.265</td>\n","      <td>286.088</td>\n","      <td>181.432</td>\n","      <td>0.169</td>\n","      <td>386.167</td>\n","      <td>29.581</td>\n","      <td>13.054</td>\n","      <td>8.15</td>\n","      <td>snort</td>\n","    </tr>\n","    <tr>\n","      <th>410</th>\n","      <td>1.511</td>\n","      <td>47.826</td>\n","      <td>302.461</td>\n","      <td>197.067</td>\n","      <td>0.549</td>\n","      <td>393.041</td>\n","      <td>25.510</td>\n","      <td>15.407</td>\n","      <td>4.52</td>\n","      <td>snort</td>\n","    </tr>\n","    <tr>\n","      <th>411</th>\n","      <td>4.978</td>\n","      <td>70.706</td>\n","      <td>211.919</td>\n","      <td>94.333</td>\n","      <td>0.669</td>\n","      <td>477.292</td>\n","      <td>29.899</td>\n","      <td>15.963</td>\n","      <td>7.78</td>\n","      <td>snort</td>\n","    </tr>\n","    <tr>\n","      <th>412</th>\n","      <td>2.142</td>\n","      <td>33.163</td>\n","      <td>142.663</td>\n","      <td>872.093</td>\n","      <td>0.514</td>\n","      <td>448.085</td>\n","      <td>30.173</td>\n","      <td>14.850</td>\n","      <td>11.90</td>\n","      <td>snort</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>413 rows × 10 columns</p>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f95f5a6a-65b0-49b9-9c26-3ea9fba10ad3')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 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Valentim","userId":"01605191331649361820"}}},"execution_count":6,"outputs":[]},{"cell_type":"markdown","source":["2) Splitting between training and test set"],"metadata":{"id":"2r7k0x0ipcV7"}},{"cell_type":"code","source":["from sklearn.ensemble import RandomForestClassifier\n","from sklearn.model_selection import train_test_split"],"metadata":{"id":"0xGuguLhpgkt"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#keith, here we can just stratify but i dont know how cause there is no variable label in the x\n","x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2, train_size = 0.8)"],"metadata":{"id":"L8G-rCNBuI_A"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["\n","Defining the model and hyperparam"],"metadata":{"id":"GIH-piYXwNaB"}},{"cell_type":"code","source":["#number of trees\n","n_estimators = [int(x) for x in np.linspace(start = 10, stop = 50, num =40)]\n","#min number of sample in each leaf\n","min_samples_split = [int(x) for x in np.linspace(15,25,10)]\n","#max number level of questions in each tree\n","max_depth = [int(x) for x in np.linspace(2,5,3)]"],"metadata":{"id":"xdUbG1KCniMI"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#hyperparam tuning\n","param_grid = {\n","    'n_estimators' : n_estimators,\n","    'min_samples_split': min_samples_split,\n","    'max_depth': max_depth\n","}\n","param_grid\n"],"metadata":{"id":"NLDu9j-gnJKh"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["I will now define the model so that we can apply that hyperparam grid"],"metadata":{"id":"8Cn2MrAssOXV"}},{"cell_type":"code","source":["model = RandomForestClassifier()"],"metadata":{"id":"gdIi__f2u9iS"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#importing the grid that allows us to tune\n","from sklearn.model_selection import GridSearchCV\n","\n","#applying the grid i created\n","rf_grid = GridSearchCV(model, param_grid, cv = 3, verbose = 2)\n","#{'max_depth': 5, 'min_samples_split': 22, 'n_estimators': 30} best one, "],"metadata":{"id":"GGyUnWPwrw57"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Now before fitting, Id like to define all the possibility of different hyperparameters"],"metadata":{"id":"FlMqlBmQmR4j"}},{"cell_type":"code","source":["rf_grid.fit(x_train,y_train)"],"metadata":{"id":"h-N6QollydVm"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["rf_grid.best_params_"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f41EY3-huixj","executionInfo":{"status":"ok","timestamp":1654296042789,"user_tz":-120,"elapsed":300,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}},"outputId":"20196276-96f8-4315-f83e-7ef3064e21d2"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'max_depth': 5, 'min_samples_split': 22, 'n_estimators': 30}"]},"metadata":{},"execution_count":48}]},{"cell_type":"code","source":["rf_grid.score(x_train, y_train)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lPdsWxaP0uau","executionInfo":{"status":"ok","timestamp":1654296068311,"user_tz":-120,"elapsed":244,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}},"outputId":"eb60ad6a-f800-43ce-9d3b-6fc9c6c5e50c"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.9151515151515152"]},"metadata":{},"execution_count":49}]},{"cell_type":"code","source":["rf_grid.score(x_test, y_test)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fKt9_oPc02fO","executionInfo":{"status":"ok","timestamp":1654296077563,"user_tz":-120,"elapsed":239,"user":{"displayName":"Matheus Valentim","userId":"01605191331649361820"}},"outputId":"2a023de3-a283-4762-a373-d607de9f98c2"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.927710843373494"]},"metadata":{},"execution_count":50}]},{"cell_type":"markdown","source":["best hyperparams: {'max_depth': 5, 'min_samples_split': 22, 'n_estimators': 30}\n","the score for training was 0.91\n","the score for test was 0.92\n","\n","gonna run a confusion matrix now"],"metadata":{"id":"HYUJ8YkHu3iH"}}]}