KFold Cross Validation using Scikit Learn | Best Model | KFold from sklearn.cross_validation

[@ranaamnan7661]

good sir
keep it up...!

[@technologyCult]

Thankyou :)

[@liangyumin9405]

def kfold_in_model_selection_modual():
from sklearn.model_selection import KFold
kf = KFold(n_splits=3, shuffle=False)
print('*' * 50, 'cross_validation', '*' * 20)
print('{}{:^51} {}'.format('Iterations', 'Training Set', 'Testing Set'))
print('*' * 50, 'cross_validation', '*' * 20)
for train_index, test_index in enumerate(kf.split(range(15))):
print(train_index, test_index)

[@_ekcup_chai]

error: __init__() got multiple values for argument 'n_folds'

[@liangyumin9405]

cross_validation model is deprecated... now use model_selection in py 3.6.6

[@technologyCult]

I will come up with kfold from model_selection 😊 .. Thankyou

[@ziemamadoucoulibaly2305]

@@technologyCult use model selection please ,my problem is fitting x_train and y_train with linear regression, have you solution about my problem??