A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Feature Selection using ReliefF Algorithm
IJARCCE - Computer and Communication Engineering
2014
IJARCCE
IJARCCE - Computer and Communication Engineering
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
doi:10.17148/ijarcce.2014.31031
fatcat:h2aa2tjkizdrblub32dzleic2a