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Reseach Article

B-cell and T-cell Leukemia Classification using Genetic Algorithm, PCA, SVM and ANN

by Sakshi Sharma, Ajay Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 46
Year of Publication: 2019
Authors: Sakshi Sharma, Ajay Kumar
10.5120/ijca2019919380

Sakshi Sharma, Ajay Kumar . B-cell and T-cell Leukemia Classification using Genetic Algorithm, PCA, SVM and ANN. International Journal of Computer Applications. 178, 46 ( Sep 2019), 36-41. DOI=10.5120/ijca2019919380

@article{ 10.5120/ijca2019919380,
author = { Sakshi Sharma, Ajay Kumar },
title = { B-cell and T-cell Leukemia Classification using Genetic Algorithm, PCA, SVM and ANN },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2019 },
volume = { 178 },
number = { 46 },
month = { Sep },
year = { 2019 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number46/30862-2019919380/ },
doi = { 10.5120/ijca2019919380 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:53:18.681314+05:30
%A Sakshi Sharma
%A Ajay Kumar
%T B-cell and T-cell Leukemia Classification using Genetic Algorithm, PCA, SVM and ANN
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 46
%P 36-41
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Microarray technology can be used for learning number of genes expressions at one time. In recent years, DNA microarray method has a large influence in deciding the informative genes which originates cancer. The important step is the extraction of relevant genes in analyzing microarray cancer data. In this paper, microarray classification is done in two phases. In the first phase, a hybrid approach of principle component analysis is and genetic algorithm is applied on leukemia microarray dataset for extracting relevant features. Feed forward back propagation neural network is used and support vector machine for the classification purpose in the second phase and finally their results are compared.

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Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction micro array gene expression principle component analysis genetic algorithms feed forward back propagation neural network support vector machine.