yanshanjing/learning-from-imbalanced-classes

Learning From Imbalanced Classes

learning-from-imbalanced-classes

This repo corresponds to a blog post I wrote discussing how to learn from data with imbalanced classes. The blog post is here: http://www.svds.com/learning-imbalanced-classes/. In this directory you'll find two Python Jupyter notebooks illustrating two points made in that blog post.

Gaussians.ipynb is an interactive notebook that allows you to play with varied sampling from two Gaussian distributions to see what logistic regression does with the points as the mixtures are varied.

ImbalancedClasses.ipynb illustrates a method called blagging (basically, downsampled bagging) on a domain called Glass from the UCI Repository. It goes through steadily more imbalanced versions of the domain, testing different algorithms and showing the results.