K-means Based Local Decomposition for Rare Class Analysis

Abstract

Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, rare class analysis remains a critical challenge, because there is no natural way developed for handling imbalanced class distributions. This chapter thus fills this crucial void by developing a method for Classification using lOcal clusterinG (COG). Specifically, for a data set with an imbalanced class distribution, we perform clustering within each large class and produce sub-classes with relatively balanced sizes.