Gene expression classification using optimal feature/classifier ensemble with negative correlation

Jungwon Ryu, Sung Bae Cho

Research output: Contribution to conferencePaperpeer-review

19 Citations (Scopus)

Abstract

In order to predict the cancer class of patients, we have illustrated a classification framework that combines sets of classifiers trained with independent two features. Experimental results show that the feature sets that have negative or non-positive correlations produces very high recognition result.

Original languageEnglish
Pages198-203
Number of pages6
Publication statusPublished - 2002
Event2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States
Duration: 2002 May 122002 May 17

Other

Other2002 International Joint Conference on Neural Networks (IJCNN '02)
CountryUnited States
CityHonolulu, HI
Period02/5/1202/5/17

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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