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I am trying to use hyperopt_search with random_forest_regression and gradient_boosting_regressor but I got the following error :
TypeError: estimator should be an estimator implementing 'fit' method, <hyperopt.pyll.base.Apply object at 0x000000000D093048> was passed
And in one of the lines error it checks if it is a classifier :
C:\user\Anaconda3\lib\site-packages\sklearn\cross_validation.py in cross_val_score(estimator, X, y, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch)
1571
1572 cv = check_cv(cv, X, y, classifier=is_classifier(estimator))
-> 1573 scorer = check_scoring(estimator, scoring=scoring)
1574 # We clone the estimator to make sure that all the folds are
1575 # independent, and that it is pickle-able.
I am wondering if the error comes from using a regressor and not a classifier.
Thank you for your help.
Regards.
The text was updated successfully, but these errors were encountered:
Hello,
I am trying to use hyperopt_search with random_forest_regression and gradient_boosting_regressor but I got the following error :
TypeError: estimator should be an estimator implementing 'fit' method, <hyperopt.pyll.base.Apply object at 0x000000000D093048> was passed
And in one of the lines error it checks if it is a classifier :
I am wondering if the error comes from using a regressor and not a classifier.
Thank you for your help.
Regards.
The text was updated successfully, but these errors were encountered: