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Chormunge, Smita
- Performance Evaluation of Feature Selection Measures
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1 Department of Computer Science and Engineering, GITAM University, Hyderabad, Telangana, IN
2 Department of Information Technology, GITAM University, Hyderabad, Telangana, IN
1 Department of Computer Science and Engineering, GITAM University, Hyderabad, Telangana, IN
2 Department of Information Technology, GITAM University, Hyderabad, Telangana, IN
Source
International Journal of Knowledge Based Computer System, Vol 4, No 2 (2016), Pagination: 29-31Abstract
Feature Selection is one of the approach for solving dimensionality problem. Numerous feature selection filter evaluation measures are used to produce good feature subset. This paper presents the comparison of Information Gain, Correlation and Gain Ratio filter measures to verify the performance of different filter evaluation measures on high dimensional datasets. Computational time required to evaluate dataset with respect to Naïve Bayes classifier is calculated by using filter measures. Experimental results on different datasets demonstrate that Correlation measure is favourable in terms of computational time than other measures.Keywords
Feature Selection, Correlation, Information Gain, Filter Measures, Gain Ratio.References
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