Multicategory Classification Using Support Vector Machine for Microarray Gene Expression Cancer Diagnosis

MRS.S.SASIKALA
MRS.S.SASIKALA * §
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Lt. Dr. S Santhosh Baboo
Lt. Dr. S Santhosh Baboo
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Dr.S.SANTHOSH BABOO
Dr.S.SANTHOSH BABOO
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I.Kadar Shereef
I.Kadar Shereef
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§ Sree Saraswathi Thyagaja College, Pollachi

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Multicategory Classification Using Support Vector Machine for Microarray Gene Expression Cancer Diagnosis

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Abstract

This paper deals with the advanced and developed methodology know for cancer multi classification using Support Vector Machine (SVM) for microarray gene expression cancer diagnosis, this is used for directing multicategory classification problems in the cancer diagnosis area. SVMs are an appropriate new technique for binary classification tasks, which is related to and contain elements of non-parametric applied statistics, neural networks and machine learning. SVMs can generate accurate and robust classification results on a sound theoretical basis, even when input data are non-monotone and non-linearly separable. The performance of SVM is evaluated for the multicategory classification on benchmark microarray data sets for cancer diagnosis, namely, the SRBCT Data set. The results indicate that SVM produces comparable or better classification accuracies when the data given as input are preprocessed. SVM delivers high performance with reduced training time and implementation complexity is less when compared to artificial neural networks methods like conventional backpropagation ANN and Linder’s SANN.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

MRS.S.SASIKALA, Dr.S.SANTHOSH BABOO, Dr.S.SANTHOSH BABOO. 1970. "Multicategory Classification Using Support Vector Machine for Microarray Gene Expression Cancer Diagnosis". Global Journal of Computer Science and Technology GJCST Volume 10 (GJCST Volume 10 Issue 15).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
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Classification
GJCST Classification J.3
H.2.8
  • Submission ReceivedFebruary 12, 2010
  • Peer Review Double Blind
    Handling Editor
  • Accepted March 2, 2010
  • Published March 15, 2010
Version of record

v1.2

Issue date
October 15, 2010

Language
English
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Multicategory Classification Using Support Vector Machine for Microarray Gene Expression Cancer Diagnosis

MRS.S.SASIKALA
MRS.S.SASIKALA Sree Saraswathi Thyagaja College, Pollachi
Dr.S.SANTHOSH BABOO
Dr.S.SANTHOSH BABOO
Dr.S.SANTHOSH BABOO
Dr.S.SANTHOSH BABOO
  • Submission ReceivedFebruary 12, 2010
  • Peer Review Double Blind
    Handling Editor
  • Accepted March 2, 2010
  • Published March 15, 2010