python - Performing grid search with a predefined validation set Sklearn -


this question has been asked several times before. error when following answer

first specify part training set , validation set follows.

my_test_fold = []   in range(len(train_x)):     my_test_fold.append(-1)   in range(len(test_x)):     my_test_fold.append(0)

and gridsearch performed. 

from sklearn.model_selection import predefinedsplit param = {  'n_estimators':[200],  'max_depth':[5],  'min_child_weight':[3],  'reg_alpha':[6],     'gamma':[0.6],     'scale_neg_weight':[1],     'learning_rate':[0.09] }     gsearch1 = gridsearchcv(estimator = xgbclassifier(      objective= 'reg:linear',      seed=1),  param_grid = param,  scoring='roc_auc', cv = predefinedsplit(test_fold=my_test_fold), verbose = 1)   gsearch1.fit(new_data_df, df_y)

but following error

 object of type 'predefinedsplit' has no len()

try replace

cv = predefinedsplit(test_fold=my_test_fold)

with

cv = list(predefinedsplit(test_fold=my_test_fold).split(new_data_df, df_y))

the reason may need apply split method split training , testing (and transform iterable object list object).


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