On the minimum probability of classification error through effective cardinality comparison
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Abstract
A straightforward ''collision'' (quadratic) entropy estimator is used to give support, in a very pragmatic approach, to data analysis based on the concept of effective cardinality of sets. Thus, by using basic concepts of probability and set theories, a method is proposed to estimate the minimum probability of classification error, in two-class problems, without the deployment of any particular classifier. The usefulness as well as some limitations of the analysis based on effective cardinality are exemplified throughout the text.
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How to Cite
Montalvão, J., Canuto, J., & Carvalho, E. (2016). On the minimum probability of classification error through effective cardinality comparison. Journal of Communication and Information Systems, 31(1). https://doi.org/10.14209/jcis.2016.26
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Regular Papers
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