Neural network ensemble with negatively correlated features for cancer classification

Hong Hee Won, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it expectedly helps us to exactly predict and diagnose cancer. It is essential to efficiently analyze DNA microarray data because the amount of DNA microarray data is usually very large. Since accurate classification of cancer is very important issue for treatment of cancer, it is desirable to make a decision by combining the results of various expert classifiers rather than by depending on the result of only one classifier. In spite of many advantages of ensemble classifiers, ensemble with mutually error-correlated classifiers has a limit in the performance. In this paper, we propose the ensemble of neural network classifiers learned from negatively correlated features to classify cancer precisely, and systematically evaluate the performance of the proposed method using three benchmark datasets. Experimental results show that the neural network ensemble with negatively correlated features produces the best recognition rate on the three benchmark datasets.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsOkyay Kaynak, Ethem Alpaydin, Erkki Oja, Lei Xu
PublisherSpringer Verlag
Pages1143-1150
Number of pages8
ISBN (Print)3540404082, 9783540404088
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2714
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Won, H. H., & Cho, S. B. (2003). Neural network ensemble with negatively correlated features for cancer classification. In O. Kaynak, E. Alpaydin, E. Oja, & L. Xu (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 1143-1150). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2714). Springer Verlag. https://doi.org/10.1007/3-540-44989-2_136