scikit learn - Ensembling with dynamic weights -

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i wondering if possible use dynamic weights in sklearn's votingclassifier. overall have 3 labels 0 = other, 1 = spam, 2 = emotion. dynamic weights mean following:

i have 2 classifiers. first 1 random forest performs best on spam detection. other 1 cnn superior topic detection (good distinction between other , emotion). votingclassifier gives higher weight rf when assigns label "spam/1".

is votingclassifier right way go?

best regards,

stefan


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