Multiclass Classification and Support Vector Machine

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Multiclass Classification and Support Vector Machine

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Abstract

In this paper we have studied the concept and need of Multiclass classification in scientific research. Various classification approaches are discussed in brief. Support Vector Machines (SVM) has well known record in Binary Classification. Our major emphasis in this paper is to study the fitness of Support Vector Machines in multiclass classification.

References

4 Cites in Article
  1. Fernando Berzal,Nicolfás Matín (2002). Data mining.
  2. O Olutayo,Gaurav Oladunni,Singhal (2009). Piecewise Multi-Classification Support Vector Machines.
  3. Chih-Wei Hsu,Chih-Jen Lin (2002). A Comparison of Methods for Multiclass Support Vector Machines.
  4. Laura Auria,Rouslan Moro (2008). Support Vector Machines (SVM) as a Technique for Solvency Analysis.

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

Yashima Ahuja. 2012. "Multiclass Classification and Support Vector Machine". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 12 (GJCST Volume 12 Issue G11).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-G Classification G.4
C.1.2
Version of record

v1.2

Issue date
December 31, 2012

Language
English
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Multiclass Classification and Support Vector Machine

Yashima Ahuja
Yashima Ahuja Lovely Professional University