Comparative Study of Different Feature Selection Algorithm in Small dataset Among KNN, FUZZY & GENETIC Algorithm.
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 7
Abstract
In the earth of curse of dimensionality feature selection acting a very important role in reducing the entire feature collection with the partial subset of features Falling the number of features pave way for a variety of advantaged as well as simplify the assignment. Feature selection means finding the appropriate set of features which will give the majority of it to the solution with minimum or null error rate. Selected features are to be tested with the help of classifiers, so that the separation of selected features can be proved to be most favorable when compared to other features subsets separately as well as a group. Genetic algorithms are now days play a very important role among any other method in selecting the features based on the Theory of Evolution and on the “Survival of the fitness”. It is a heuristic approach. To cooperate with the GA approach we have the classifiers which will go hand in hand to bring out the final set of features along with their calculation accuracy. In this paper we have analyze, classifiers and compare them with their act and the unit of correctness.
Authors and Affiliations
Lal Bahadur Pandey, , Siddharth Choubey,
Keywords
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