python - sklearn: How to reset a Regressor or classifier object in sknn -


i have defined regressor follows:

nn1 = regressor( layers=[     layer("rectifier", units=150),     layer("rectifier", units=100),     layer("linear")], regularize="l2", # dropout_rate=0.25, learning_rate=0.01, valid_size=0.1, learning_rule="adagrad", verbose=false, weight_decay=0.00030, n_stable=10, f_stable=0.00010, n_iter=200)

i using regressor in k-fold cross-validation. in order cross-validation work , not learn previous folds, it's necessary regressor reset after each fold.
how can reset regressor object?

sklearn.base.clone should achieve you're looking achieve


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