"The train-test split is stratified to ensure that the train and test samples from each class are almost the same percentage. This may be desirable for imbalanced number of samples as in this case. \n",
"\n",
"In such imbalanced datasets, the stratified K fold cross validation is used instead of the K-fold cross validation"
"C:\\Users\\60172\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\sklearn\\base.py:439: UserWarning: X does not have valid feature names, but GradientBoostingClassifier was fitted with feature names\n",
The train-test split is stratified to ensure that the train and test samples from each class are almost the same percentage. This may be desirable for imbalanced number of samples as in this case.
In such imbalanced datasets, the stratified K fold cross validation is used instead of the K-fold cross validation
C:\Users\60172\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\sklearn\base.py:439: UserWarning: X does not have valid feature names, but GradientBoostingClassifier was fitted with feature names