Paper Title

INDECISIVE CONDITION CLASSIFICATION USING SVM

Authors

  • Jyoti Pathak
  • Sachin Patel

Keywords

support vector machine, indecisive data, associative classification, fuzzy clustering.

Abstract

In this research, we exploit the regularize framework and proposed an associative classification algorithm for uncertain data. The major recompense of SVM(support vector machine) are: recurrent item sets capture every dominant associations between items in a dataset. These classifiers naturally handle missing values and outliers as they only deal with statistically significant associations which build the classification to be vigorous. We proposed a novel indecisive SVM Based clustering algorithm which considers large databases as the major application. The SVM Based clustering algorithm will cluster a specified set of data and exploit the matching which proposes other works.

Article Type

Published

How To Cite

Jyoti Pathak, Sachin Patel. "INDECISIVE CONDITION CLASSIFICATION USING SVM".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 1, pp.688-693, URL :https://rjwave.org/ijedr/papers/IJEDR1401125.pdf

Issue

Volume 2 Issue 1 

Pages. 688-693

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