sir kl wala code nhi mila

[Saibtain]

kia kisi ko kal wala code mila jo sir na kha tha k ma code send kr doon ga

[usamabajwa86]

libraries and model import

import numpy as np
from sklearn.model_selection import train_test_split, cross_val_score

from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.svm import SVC

define the models to be evaluated

models = [LogisticRegression(), KNeighborsClassifier(), RandomForestClassifier(), SVC()]
names = ["Logistic Regression", "KNN", "Random Forest", "SVM"]

perform k-fold cross-validation for each model

k = 10
for name, model in zip(names, models):
cv_scores = cross_val_score(model, X_train, y_train, cv=k)
print(f"{name} CV accuracy: {np.mean(cv_scores):.3f} +/- {np.std(cv_scores):.3f}")

[usamabajwa86]

from sklearn.model_selection import GridSearchCV

Define the parameter grid

param_grid = {'C': [0.1, 1, 10],
'kernel': ['linear', 'rbf'],
'gamma': [0.1, 1, 10]}

grid_search = GridSearchCV(SVC(), param_grid, cv=5)
grid_search.fit(X_train, y_train)

print("Best parameters: {}".format(grid_search.best_params_))
print("Best cross-validation score: {:.2f}".format(grid_search.best_score_))

[Muhammad-Ali-Butt]

@Saibtain bhai agar best model selection walay ki baat kr rai ho jo kal raat kia ha wo mujhay b ni mila github par kahi but maine wo video dobara dekhi aur code saath saath likh lia its only 23 mins long video.

https://youtu.be/XiUJwXglo5s

[nouman073]

I wrote code from video but my output showing like that

[AzamBukhari]

@nouman073 bhai, ap neechey wali line mai model_name ki juga model_names istemal ker rahey hain

models_scores.append([model_name,accuracy])