Using sklearn voting ensemble with partial fit

Question

Can someone please tell how to use ensembles in sklearn using partial fit. I don\'t want to retrain my model. Alternatively, can we pass pre-trained models for ensembling ?

Answer 1

It's not too hard to implement the voting. Here's my implementation:

import numpy as np 

class VotingClassifier(object):
    """ Implements a voting classifier for pre-trained classifiers"""

    def __init__(self, estimators):
        self.estimators = estimators

    def predict(self, X):
        # get values
        Y = np.zeros([X.shape[0], len(self.estimators)], dtype=int)
        for i, clf in enumerate(self.estimators):
            Y[:, i] = clf.predict(X)
        # apply voting 
        y = np.zeros(X.shape[0])
        for i in range(X.shape[0]):
            y[i] = np.argmax(np.bincount(Y[i,:]))
        return y