Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic

T.Jaga Priya Vathana; C.Saravanabhavan; Dr. J.Vellingiri

Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic

T.Jaga Priya Vathana * §

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C.Saravanabhavan

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Dr. J.Vellingiri

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§ Kongunadu College of Engineering and Technology/Anna...

Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic

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Abstract

Feature subset selection is an effective way for reducing dimensionality, removing irrelevant data, increasing learning accuracy and improving results comprehensibility. This process improved by cluster based FAST Algorithm and Fuzzy Logic. FAST Algorithm can be used to Identify and removing the irrelevant data set. This algorithm process implements using two different steps that is graph theoretic clustering methods and representative feature cluster is selected. Feature subset selection research has focused on searching for relevant features. The proposed fuzzy logic has focused on minimized redundant data set and improves the feature subset accuracy.

References

8 Cites in Article

Reference Format

Hussein Almuallim,Thomas Dietterich (1992). On Learning More Concepts.
H Almuallim,T Dietterich (1994). Learning boolean concepts in the presence of many irrelevant features.
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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

T.Jaga Priya Vathana, C.Saravanabhavan, Dr. J.Vellingiri. 2013. "Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C10).

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GJCST Volume 13 Issue C10

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

GJCST-C Classification I.5

Submission ReceivedDecember 7, 2012
Peer Review Double Blind
Handling Editor
Accepted December 31, 2012
Published January 15, 2013

Version of record

v1.2

Issue date

October 5, 2013

Language

English

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Article Matrices

Total Score: 148

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: T.Jaga Priya Vathana, C.Saravanabhavan, Dr. J.Vellingiri (PhD/Dr. count: 1)

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Publish Date: 2013 01, Tue

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Total Downloads: 103

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