Evaluating the Stability of Feature Selectors That Optimize Feature Subset Cardinality

Authors:
Petr Somol;Jana Novovičová
Affiliations:
Dept. of Pattern Recognition, Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic 182 08 and Faculty of Management, Prague University ...;Dept. of Pattern Recognition, Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic 182 08 and Faculty of Management, Prague University ...
Venue:
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2008

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Abstract

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.