How to find the corresponding class in clf.predict_proba()

Question

I have a number of classes and corresponding feature vectors, and when I run predict_proba() I will get this:

classes = ['one','two','three','one','three']

feature = [[0,1,1,0],[0,1,0,1],[1,1,0,0],[0,0,0,0],[0,1,1,1]]

from sklearn.naive_bayes import BernoulliNB

clf = BernoulliNB()

clf.fit(feature,classes)

clf.predict_proba([0,1,1,0])

>> array([[ 0.48247836,  0.40709111, 0.11043053]])

I would like to get what probability that corresponds to what class. On this page it says that they are ordered by arithmetical order, I'm not 100% sure of what that means: http://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html#sklearn.svm.SVC.predict_proba

Does it mean that I have gone through my training examples assign the corresponding index to the first encounter of a class, or is there a command like

clf.getClasses() = ['one','two','three']

Answer 1

You can simply use .classes_ attributes of the classifier to recover the mapping of classes. 

For example:

>>> clf.classes_

array(['one', 'three', 'two'], 

      dtype='|S5')

Your short and optimal question helped me answer faster.

Hope this answer helps.

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