Abstract
We discuss the notion of risk in generally understood classification support systems. We consider the situation when granularity is involved in information system we work with. We propose a method for approximating the loss function and introduce a technique for assessing the empirical risk from experimental data. We discuss the general methodology and possible directions of development in the area of constructing compound classification schemes. © 2009 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Szczuka, M. (2009). Approximation of loss and risk in selected granular systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5908 LNAI, pp. 168–175). https://doi.org/10.1007/978-3-642-10646-0_20
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