Genome Based Classification of Human Papilloma Virus Using Linear Discriminant Analysis

Authors

  • Swain S Department of Computer Science, Berhampur University, Berhampur, Odisha, India
  • Patra MR Department of Computer Science, Berhampur University, Berhampur, Odisha, India

Keywords:

Genome, Genes, HPV, LDA, Papillomaviridae, Multivariate analysis, Univariate analysis

Abstract

Biological classification of Papillomaviridae leads to several hundred different genera (classes) of Human Papilloma Viruses (HPV) that are discriminated on the basis of more than hundred different characteristics. Statistical procedures of classification based on genome and gene size are being applied to biologically define different class labels for HPV. In this paper, Fisher’s linear discriminant analysis (LDA) has been used for classification of HPV on the basis of total genome size and gene sizes. Univariate and multivariate modes of classification have been employed to recognize two distinct classes of HPV viz., alpha- papilloma and beta-papilloma that cause cervical cancer in humans. The aim is to build a classification model so as to predict unknown samples. The accuracy of the proposed model has been measured on a sample dataset

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Published

2025-11-24

How to Cite

[1]
S. Swain and M. Patra, “Genome Based Classification of Human Papilloma Virus Using Linear Discriminant Analysis”, Int. J. Comp. Sci. Eng., vol. 7, no. 3, pp. 192–196, Nov. 2025.

Issue

Vol. 7 No. 3 (2019): IJCSE Special Issue Feb Edition

Section

Research Article

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