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MEMBERS OF RESEARCH CENTER
Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Publications
Evaluating the Stability of Feature Selectors that Optimize Feature Subset Cardinality
Typ:
Jornal article
Authors:
Name of journal:
Lecture Notes in Computer Science
Year:
2008
Number:
5342 (2008)
Pages:
956-966
ISSN:
0302-9743
Keywords:
Feature selection, stability, relative weighted consistency
Anotation:
Stability (robustness) of feature selection methods is a topic of recent interest. Unlike other known stability criteria, the new consistency measures proposed in this paper evaluate the overall occurrence of individual features in selected subsets of possibly varying cardinality. The new measures are compared to the generalized Kalousis measure which evaluates pairwise similarities between subsets. The new measures are computationally very effective and offer more than one type of insight into the stability problem. All considered measures have been used to compare two standard feature selection methods on a set of examples.