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Diseases classification using support vector machine (SVM)

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4 Author(s)
Liu Sheng ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore ; Song Qing ; Hu Wenjie ; Cao Aize

The paper proposed a new method: disease classification based on protein sequence. Support vector machine was used for this problem and a new encoding for the multicode protein sequence was suggested. Two extracted features were selected for classifying, the results showed the capability of SVM for such bioinformatics problems and the goodness of the system of protein sequence based disease classification. It gave error around 4-5%, which presented that although it is good for such problems, improvement of the algorithm also should be made.

Published in:

Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on  (Volume:2 )

Date of Conference:

18-22 Nov. 2002