E LAS-Relief-A Novel Feature Selection Algorithm In Data mining
Keywords:
Data mining, Relief algorithm, feature selection, Naive Bayes, J48 classifiersAbstract
Feature selection is vital task in any data mining pre-processing procedure. This paper deals with the problem of estimating the quality features in the feature sets. The original feature estimating algorithm LAS-Relief algorithm can deal with discrete and continues attributes and it is limited to irrelevant feature removal. The new improved feature selection technique called E LAS-Relief deals with noisy and incomplete data sets. This paper shows that the novel algorithm E LAS-Relief outperforms on agriculture soil data sets for classification.
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