Abstract
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.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Day, W. H., & Edelsbrunner, H. (1984). Efficient algorithms for agglomerative hierarchical clustering methods. Journal of Classification, 1(1), 7–24.
Jakulin, A. (2005) Machine learning based on attribute interactions. PhD thesis, University of Ljubljana. http://eprints.fri.uni-lj.si/205/
Kira, K., & Rendell, L. A. (1992). The feature selection problem: Traditional methods and a new algorithm. In AAAI (pp. 129–134). Cambridge: AAAI Press/MIT Press.
Kononenko, I. (1994). Estimating attributes: Analysis and extensions of Relief. In Bergadano, F., & Raedt, L. D. (Eds.) Lecture notes in computer science : Vol. 784. ECML (pp. 171–182). Berlin: Springer.
Kononenko, I., & Šikonja, M. R. (2007). Non-myopic feature quality evaluation with (R)ReliefF. In Liu, H., & Motoda, H. (Eds.) Computational methods of feature selection. Boca Raton: Chapman & Hall/CRC.
Kramer, S. (1994) CN2-MCI: A two-step method for constructive induction. In: Proc. ML-COLT ’94 workshop on constructive induction and change of representation, New Brunswick, New Jersey.
Šikonja, M. R., & Kononenko, I. (2003). Theoretical and empirical analysis of ReliefF and RReliefF. Machine Learning, 53(1–2), 23–69.
Author information
Authors and Affiliations
Corresponding author
Additional information
Editor: Hendrik Blockeel.
Rights and permissions
About this article
Cite this article
Demšar, J. Algorithms for subsetting attribute values with Relief. Mach Learn 78, 421–428 (2010). https://doi.org/10.1007/s10994-009-5164-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10994-009-5164-0