Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic

1
T.Jaga Priya Vathana
T.Jaga Priya Vathana
2
C.Saravanabhavan
C.Saravanabhavan
3
Dr. J.Vellingiri
Dr. J.Vellingiri
1 Kongunadu College of Engineering and Technology/Anna University Chennai

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Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic Banner
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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.

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No external funding was declared for this work.

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The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Not applicable for this article.

T.Jaga Priya Vathana. 2013. \u201cFeature Selection Algorithm for High Dimensional Data using Fuzzy Logic\u201d. 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
Pg. 47- 56
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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October 5, 2013

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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.

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Feature Selection Algorithm for High Dimensional Data using Fuzzy Logic

T.Jaga Priya Vathana
T.Jaga Priya Vathana Kongunadu College of Engineering and Technology/Anna University Chennai
C.Saravanabhavan
C.Saravanabhavan
Dr. J.Vellingiri
Dr. J.Vellingiri

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