RADIAL BASIS FUNCTION-PARTICLE SWARME OPTIMIZATION ALGORITHM FOR FEATURE REDUCTION (RBF-PSO)
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Abstract
-Feature Reduction is an important step in data mining technique which removes unwanted attributes. The feature selection technique is used in various research fields. In this paper a hybrid algorithm named Radial Basis Function-Particle Swarm Optimization (RBF-PSO) Algorithm is proposed by combining the two existing algorithms, Radial Basis Function and Particle Swarm Optimization Algorithm. The result obtained proves that the proposed algorithm work well for Feature Reduction when comparing with the existing algorithms.
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