Best way to combine probabilistic classifiers in scikit-learn
classification, machine-learning, python, scikit-learn
Solution
NOTE: The scikit-learn Voting Classifier is probably the best way to do this now
OLD ANSWER:
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)
Problem
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. 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?