An Efficient Multi-class Support Vector Machine Classifier for Protein Fold Recognition

被引：4
|
作者：
Chmielnicki, Wieslaw
Stapor, Katarzyna
Roterman-Konieczna, Irena
机构：
来源：
ADVANCES IN BIOINFORMATICS | 2010年 / 74卷
关键词：
ENSEMBLE; SCOP;
D O I：
10.1007/978-3-642-13214-8_10
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
Predicting the three-dimensional (3D) structure of a protein is a key problem in molecular biology. It is also interesting issue for statistical methods recognition. In this paper a multi-class Support Vector Machine (SVM) classifier is used on a real world data set. The SVM is a binary classifier and how to effectively extend a binary to the multi-class classifier case is still an on-going research problem. The new efficient approach is proposed in this paper. The obtained results are promising and reveal areas for possible further work.
引用
收藏
页码：77 / 84
页数：8
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