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ICML
2008
IEEE

Multi-classification by categorical features via clustering

10 years 6 months ago
Multi-classification by categorical features via clustering
We derive a generalization bound for multiclassification schemes based on grid clustering in categorical parameter product spaces. Grid clustering partitions the parameter space in the form of a Cartesian product of partitions for each of the parameters. The derived bound provides a means to evaluate clustering solutions in terms of the generalization power of a built-on classifier. For classification based on a single feature the bound serves to find a globally optimal classification rule. Comparison of the generalization power of individual features can then be used for feature ranking. Our experiments show that in this role the bound is much more precise than mutual information or normalized correlation indices.
Yevgeny Seldin, Naftali Tishby
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2008
Where ICML
Authors Yevgeny Seldin, Naftali Tishby
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