Feature Selection using ReliefF Algorithm
R. P. L. Durgabai, RAVI BHUSHAN Y · IJARCCE · 2014
Feature Selection is the preprocessing process of identifying the subset of data from large dimension data.To identifying the required data, using some Feature Selection algorithms.Like Relief, Parzen-Relief algorithms, it attempts to directly maximize the classification accuracy and naturally reflects the Bayes error in the objective.In this paper a new algorithm is proposed determine feature selection with error minimization.Proposed algorithmic framework selects a subset of features by minimizing the Bayes error rate estimated by a nonparametric estimator.