An entropy measure for the complexity of multi-output Boolean functions
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
C4.5: programs for machine learning
C4.5: programs for machine learning
A characterization of the information content of a classification
Information Processing Letters
Functional Entropy and Decision Trees
ISMVL '98 Proceedings of the The 28th International Symposium on Multiple-Valued Logic
On Axiomatization of Conditional Entropy of Functions Between Finite Sets
ISMVL '99 Proceedings of the Twenty Ninth IEEE International Symposium on Multiple-Valued Logic
An axiomatization of partition entropy
IEEE Transactions on Information Theory
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We discuss several axiomatizations of entropy and some of its generalizations using an algebraic approach. The entropy is defined for such objects as functions, partitions, and set collections and the axiomatizations use natural operations on such objects. The generalizations of entropy we propose have applications in circuit design, data mining, machine learning, and information retrieval.