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E LAS-Relief-A Novel Feature Selection Algorithm In Data mining

S.S. Baskar, L Arockiam


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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