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.
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Somol, P., Novovičová, J. (2008). Evaluating the Stability of Feature Selectors That Optimize Feature Subset Cardinality. In: da Vitoria Lobo, N., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science, vol 5342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89689-0_99
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DOI: https://doi.org/10.1007/978-3-540-89689-0_99
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