DocumentCode
394146
Title
Diseases classification using support vector machine (SVM)
Author
Sheng, Liu ; Qing, Song ; Wenjie, Hu ; Aize, Cao
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume
2
fYear
2002
fDate
18-22 Nov. 2002
Firstpage
760
Abstract
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.
Keywords
biology computing; diseases; feature extraction; medical computing; proteins; support vector machines; SVM; bioinformatics problems; disease classification; multicode protein sequence; protein sequence; support vector machine; Bioinformatics; Biological information theory; Data mining; Diseases; Genomics; Machine learning; Protein sequence; Sequences; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN
981-04-7524-1
Type
conf
DOI
10.1109/ICONIP.2002.1198160
Filename
1198160
Link To Document