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Algorithms for subsetting attribute values with Relief

delete2009-12-22
delete12
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OA
AI
J
Janez Demšar *
DOI：10.1007/s10994-009-5164-0delete
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Abstract

Abstract

En 中文
Relief is a measure of attribute quality which is often used for feature subset selection. Its use in induction of classification trees and rules, discretization, and other methods has however been hindered by its inability to suggest subsets of values of discrete attributes and thresholds for splitting continuous attributes into intervals. We present efficient algorithms for both tasks.
Keywords:
Machine learning
Attribute quality estimation
Relief

Journal

Machine Learning cover
Machine Learning
IF:
2.9
Papers:
2.6K
Citations:
3.4W

Organization

No organization information available