Answers for "use 10 fold cross validation with sklearn"

0

sklearn kfold

from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import KFold

# Regressor
lrg = LinearRegression()

#Param Grid
param_grid=[{
 'normalize':[True, False] 
}]

# Grid Search with KFold, not shuffled in this example
experiment_gscv = GridSearchCV(lrg, param_grid, 
                               cv=KFold(n_splits=4, shuffle=False), 
                               scoring='neg_mean_squared_error')
Posted by: Guest on November-04-2020

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