@jil

The Influence of Class Imbalance on Cost-Sensitive Learning: An Empirical Study

, and . Data Mining, 2006. ICDM '06. Sixth International Conference on, page 970-974. (December 2006)
DOI: 10.1109/ICDM.2006.158

Abstract

In real-world applications the number of examples in one class may overwhelm the other class, but the primary interest is usually on the minor class. Cost-sensitive learning has been deeded as a good solution to these class-imbalanced tasks, yet it is not clear how does the class-imbalance affect cost-sensitive classifiers. This paper presents an empirical study using 38 data sets, which discloses that class-imbalance often affects the performance of cost-sensitive classifiers: When the misclassification costs are not seriously unequal, cost-sensitive classifiers generally favor natural class distribution although it might be imbalanced; while when misclassification costs are seriously unequal, a balanced class distribution is more favorable.

Description

IEEE Xplore Full-Text HTML : The Influence of Class Imbalance on Cost-Sensitive Learning: An Empirical Study

Links and resources

Tags

community

  • @dblp
  • @jil
@jil's tags highlighted