First, we split the dataset using stratify parameter
train_test_split(np.array(X), y, train_size=TRAIN_SIZE, stratify=y, random_state=42)
and then apply KFlod Cross Validation
kfold = KFold(n_splits=num_folds, shuffle=True)
fold_no = 1
for train, test in kfold.split(inputs, targets):
Does this code have any drawbacks?
