The effect of imbalanced data sets on LDA: A theoretical and empirical analysis

This paper demonstrates that the imbalanced data sets have a negative effect on the performance of LDA theoretically. This theoretical analysis is confirmed by the experimental results: using several sampling methods to rebalance the imbalanced data sets, it is found that the performances of LDA on balanced data sets are superior to those of LDA on imbalanced data sets. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.