Tomasz Maszczyk and Wlodzislaw Duch
Department of Informatics, Nicolaus Copernicus University, Grudziadzka 5, 87-100 Torun, Poland.
Shannon entropy used in standard top-down decision trees
does not guarantee the best generalization. Split criteria based on generalized
entropies offer different compromise between purity of nodes and
overall information gain. Modified C4.5 decision trees based on Tsallis
and Renyi entropies have been tested on several high-dimensional microarray
datasets with interesting results. This approach may be used in
any decision tree and information selection algorithm.
Key words: Decision rules, entropy, information theory, information selection, decision trees.
Preprint for comments in PDF, 111 KB.
Reference: Maszczyk T, Duch W,
Comparison of Shannon, Renyi and Tsallis Entropy used in Decision Trees.
Lecture Notes in Computer Science, Vol. xxx, pp. xxx-yyy, 2008
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