Year : 2022, Volume : 12, Issue : 2
First page : ( 33) Last page : ( 37)
Print ISSN : 2319-2186. Online ISSN : 2322-0996. Published online : 2022  12.
Article DOI : 10.5958/2322-0996.2022.00016.3

Identification of informative genes based on SVM-RFE method

Sharma Nitesh Kumar, Mishra Dwijesh Chandra^*

Division of Agricultural Bioinformatics, ICAR-IASRI, Pusa, New Delhi, India

^*Corresponding Author: dwijesh.mishra@icar.gov.in

Online Published on 12 September, 2023.

Received:  01  ,  2022; :  12  ,  2022; Accepted:  20  ,  2022; :  01  ,  2022.

Abstract

Feature selection is one of the important aspect of data reduction and efficient performance of classification. The aim of feature selection is to select a small subset of a feature from larger pool, rendering not only a good performance of classification but also biologically meaningful insights. The high performance implementations of machine learning algorithms have been enhanced by recent developments in programming. The support vector machine recursive feature elimination (SVM-RFE) is one of the most effective feature selection methods which have been successfully used in selecting informative genes. As Selection of a subset of informative genes from microarray data is a critical step in data analysis.

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Keywords

Support vector machine, Gene expression data, Feature selection.

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