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Feature Selection is the process where you automatically or manually select those features which contribute most to your prediction variable or output in which you are interested. Xverse is the python package for machine learning to assist Data Scientists with feature transformation and feature selection. The most popular feature selection methods are Pearson’s correlation coefficient, Spearman's rank coefficient and Chi-Squared test. When an algorithm picks a feature, it gives a vote for that feature, Xverse calculates the total votes for each feature and then picks the best ones based on votes.