Analysis of Sequence Based Classifier Prediction for HIV Subtypes

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Author(s) S. Santhosh Kumar | E. Ramaraj
Pages 1753-1758
Volume 2
Issue 10
Date October, 2012
Keywords HIV, ID3, LDA, SVM, C4.5, Sensitivity and Specificity

Abstract

Human immunodeficiency virus (HIV) is a lent virus that causes acquired immunodeficiency syndrome (AIDS). The main drawback in HIV treatment process is its sub type prediction. The sub type and group classification of HIV is based on its genetic variability and location. HIV can be divided into two major types, HIV type 1 (HIV-1) and HIV type 2 (HIV-2). Many classifier approaches have been used to classify HIV subtypes based on their group, but some of cases are having two groups in one; in such cases the classification becomes more complex. The methodology used is this paper based on the HIV sequences. For this work several classifier approaches are used to classify the HIV1 and HIV2. For implementation of the work a real time patient database is taken and the patient records are experimented and the final best classifier is identified with quick response time and least error rate.

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