Theoretical and Empirical Analysis of ReliefF and RReliefF
Theoretical and Empirical Analysis of ReliefF and RReliefF
M. Robnik-Sikonja,I. Kononenko
2003 · DOI: 10.1023/A:1025667309714
Machine-mediated learning · 2,895 citaten
TLDR
How and why Relief algorithms work, their theoretical and practical properties, their parameters, what kind of dependencies they detect, how do they scale up to large number of examples and features, how to sample data for them, how robust are they regarding the noise, how irrelevant and redundant attributes influence their output and how different metrics influences them.
