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

Authors

  • Baskar SS Research Scholar, Dept. of Computer Science, St. Joseph’s College (Autonomous), Trichirappalli, India
  • Arockiam L Associate professor, Dept. of Computer Science St. Joseph’s College (Autonomous), Trichirappalli, India

Keywords:

Data mining, Relief algorithm, feature selection, Naive Bayes, J48 classifiers

Abstract

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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Published

2024-02-26

How to Cite

Baskar, S., & Arockiam, L. (2024). E LAS-Relief-A Novel Feature Selection Algorithm In Data mining. COMPUSOFT: An International Journal of Advanced Computer Technology, 2(12), 391–395. Retrieved from https://ijact.in/index.php/j/article/view/68

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Section

Original Research Article