python 3.x - Giving multiple pipelines as input to Voting Classifier - sklearn -
i trying build voting classifier multiple pipelines input. pretty new @ this. following code using:
clf1 = multinomialnb(alpha= 0.99, fit_prior= true) clf2 = pipeline([('vect', countvectorizer(max_features=5000,ngram_range=(1,2))), ('tfidf', tfidftransformer(use_idf= true)), ('clf', sgdclassifier(alpha=0.001,learning_rate='optimal',loss= 'epsilon_insensitive' ,penalty= 'l2',n_iter = 100, random_state=42))]) clf3 = pipeline([('vect', countvectorizer(max_features=3500)), ('tfidf', tfidftransformer(use_idf=false)), ('clf', svc(random_state= 42,kernel="linear",degree=1,decision_function_shape=none))]) clf4 = pipeline([('vect', countvectorizer(max_features = 4000)), ('tfidf', tfidftransformer(use_idf=false)), ('clf', randomforestclassifier(random_state = 42,criterion="entropy"))]) eclf = votingclassifier(estimators=[('mnb', clf1), ('sgd', clf2), ('svm', clf3), ('rf',clf4)], voting='hard') eclf = eclf.fit(train_data,train_label) p = eclf.predict(test_data) np.mean(p==test_class)
the code builds 4 classifiers- multnomial naive bayes, sgd classifier, svm linear kernel , random forest classifier. when try fit data gives me following error:
could not convert string float: "training string here"
if try call fit on individual classifiers, mode runs fine. can please this?
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