UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 2
February-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRFE06038


Registration ID:
316940

Page Number

210-215

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Title

A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification

Abstract

Feature clustering is an efficient method for classification tasks that minimises the dimensionality of retrieved features. A Divisive Information-Theoretic Feature Clustering Algorithm for feature clustering is provided. The words in a document set's feature vector are sorted into clusters based on a similarity test. A cluster is formed by grouping words with similar meanings. Each cluster is distinguished by a membership function with a statistical mean and deviation. When some of the sentences are entered, the algorithm generates the necessary number of clusters. Each cluster has one extracted feature. A weighted combination of the cluster's phrases is used to extract the feature that corresponds to a cluster. This approach produces membership functions that closely match and properly represent the real distribution of the training data. Furthermore, the user is not required to specify the number of extracted features in advance, removing the need for trial-and-error to find the appropriate number of extracted features. Experiments show that it can extract attributes more quickly and correctly than earlier methods.

Key Words

A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification

Cite This Article

"A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.210-215, February-2019, Available :http://www.jetir.org/papers/JETIRFE06038.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp210-215, February-2019, Available at : http://www.jetir.org/papers/JETIRFE06038.pdf

Publication Details

Published Paper ID: JETIRFE06038
Registration ID: 316940
Published In: Volume 6 | Issue 2 | Year February-2019
DOI (Digital Object Identifier):
Page No: 210-215
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162


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