Comments (4)
Hi,
have you tried to provide classifier-pipelines as input? E.g.,
mlp = Pipeline([('std', StandardScaler()),
('mlp', MultiLayerPerceptron())])
Pls let me know if it works.
Or in case of the random forest, it may be easiest to train it with the scaled data as well (should yield the same results).
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Thanks for the reply!
I will look into your suggestion
from mlxtend.
I get very similar results using scaled data across the board. I can now use the EnsembleClassifier. Thanks again!
from mlxtend.
Cool, I am happy to hear that it worked out for you!
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