在scikit-learn中组合概率分类器的最佳方法 [英] Best way to combine probabilistic classifiers in scikit-learn

问题描述

我有一个逻辑回归和一个随机森林，我想将它们结合起来(合奏)以通过取平均值来进行最终的分类概率计算.

I have a logistic regression and a random forest and I'd like to combine them (ensemble) for the final classification probability calculation by taking an average.

在sci-kit学习中是否有内置的方法可以做到这一点?我可以以某种方式将两者的集合用作分类器吗?还是我需要推出自己的分类器?

Is there a built-in way to do this in sci-kit learn? Some way where I can use the ensemble of the two as a classifier itself? Or would I need to roll my own classifier?

推荐答案

注意:

NOTE: The scikit-learn Voting Classifier is probably the best way to do this now

旧答案:

出于什么价值，我最终这样做如下:

For what it's worth I ended up doing this as follows:

class EnsembleClassifier(BaseEstimator, ClassifierMixin):
    def __init__(self, classifiers=None):
        self.classifiers = classifiers

    def fit(self, X, y):
        for classifier in self.classifiers:
            classifier.fit(X, y)

    def predict_proba(self, X):
        self.predictions_ = list()
        for classifier in self.classifiers:
            self.predictions_.append(classifier.predict_proba(X))
        return np.mean(self.predictions_, axis=0)

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