Analysis of HCV’s Linearity Using Support Vector Machine (SVM)

Abstract:

As the stage of bioinformatics has been upgraded, classification of certain pathogen has been improved into a new manner. The main topic of this research is genetic singularity of HCV (Hepatitis C Virus) and our objective is to assay features of the HCV's amino acid under usage of Support Vector Machine (SVM) algorithm. HCV data used in our experiment has 10 kinds of sequences and 257 kinds of data. According to data analysis, some peculiar genetic patterns of HCV’s linearity that discord pre-existing neural network and C5.0 were found.

• Periodical: Applied Mechanics and Materials (Volumes 548-549)
• Pages: 1265-1269
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.548-549.1265
• Online since: April 2014
• Authors: Yun Sik Hwang*, Byeong Joo Jun, Tae Seon Yoon
• Keywords: Accuracy, HCV, Linearity, Precision, Prediction, Recall, Support Vector Machine (SVM), Training

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