Introduction to feature subset selection method |
Author(s): |
| Hemal Patel , Kalol Institute of Technology And Research Center; Mr. Lokesh Gagnani, KITRC; Mrs. Mansi Parmar, KITRC |
Keywords: |
| Classification, Particle Swarm Optimization (PSO) Rough Sets, Feature Selection (FS) |
Abstract |
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Data Mining is a computational progression to ascertain patterns in hefty data sets. It has various important techniques and one of them is Classification which is receiving great attention recently in the database community. Classification technique can solve several problems in different fields like medicine, industry, business, science. PSO is based on social behaviour for optimization problem. Feature Selection (FS) is a solution that involves finding a subset of prominent features to improve predictive accuracy and to remove the redundant features. Rough Set Theory (RST) is a mathematical tool which deals with the uncertainty and vagueness of the decision systems. |
Other Details |
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Paper ID: IJSRDV3I100412 Published in: Volume : 3, Issue : 10 Publication Date: 01/01/2016 Page(s): 527-530 |
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