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

被引：69

作者：

Xie, Jigang ^{[1
]}

Qiu, Zhengding ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Inst Informat Sci, Beijing 100044, Peoples R China

来源：

PATTERN RECOGNITION | 2007年 / 40卷 / 02期

关键词：

imbalanced data sets; linear discriminant analysis (LDA); random sampling; tomek links; smote;

D O I：

10.1016/j.patcog.2006.01.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：557 / 562

页数：6

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