Learning misclassification costs for imbalanced datasets, application in gene expression data classification

Huijuan Lu, Yige Xu, Minchao Ye, Ke Yan, Qun Jin, Zhigang Gao

研究成果: Conference contribution

抄録

Cost-sensitive algorithms have been widely used to solve imbalanced classification problem. However, the misclassification costs are usually determined empirically, leading to uncertain performance. Hence an effective method is desired to automatically calculate the optimal cost weights. Targeting at the highest weighted classification accuracy (WCA), we propose two approaches to search for the optimal cost weights, including grid searching and function fitting. In experiments, we classify imbalanced gene expression data using extreme learning machine to test the cost weights obtained by the two approaches. Comprehensive experimental results show that the function fitting is more efficient which can well find the optimal cost weights with acceptable WCA.

本文言語English
ホスト出版物のタイトルIntelligent Computing Theories and Application - 14th International Conference, ICIC 2018, Proceedings
編集者Prashan Premaratne, Phalguni Gupta, De-Shuang Huang, Vitoantonio Bevilacqua
出版社Springer Verlag
ページ513-519
ページ数7
ISBN(印刷版)9783319959290
DOI
出版ステータスPublished - 2018
イベント14th International Conference on Intelligent Computing, ICIC 2018 - Wuhan, China
継続期間: 2018 8 152018 8 18

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10954 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other14th International Conference on Intelligent Computing, ICIC 2018
CountryChina
CityWuhan
Period18/8/1518/8/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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