Probabilistic Majority Voting

Generic Majority Judgement Voting procedure for probabilities of categories in machine learning

Usage

To install through PyPI in command line

pip install majorityvoting

And to use majority judgement voting in your code

from majorityvoting import MajorityVoting

voter = MajorityVoting.Voter(probabilities, categories)
indices, names = voter.vote(windows=5)

The initializer takes in 2 arguments

• probabilities - a numpy.ndarray of lists (2d array) with equal length, each embedded list contains the probability of categories predicted by some machine learning algorithm, exactly the same you will get from scikit-learn's predict_proba() function
• categories - a list of names of categories, each category must match the index of it's probability in each and every embedded list in probabilities

TODOs

1. It's a pain to manually check the size of the lists and embedded ones, will require input argument to be pandas.DataFrame type in the next version