This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.
unbalanced
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning - scikit-learn-contrib/imbalanced-learn
Consider a problem where you are working on a machine learning classification problem. You get an accuracy of 98% and you are very happy. But that happiness doesn’t last long when you look at the confusion matrix and realize that majority class is 98% of the total data and all examples are classified as majority… Read More »Handling imbalanced dataset in supervised learning using family of SMOTE algorithm.
Imbalanced classes put "accuracy" out of business. This is a surprisingly common problem in machine learning, and this guide shows you how to handle it.