In classification problems, lack of knowledge of the prior distribution may make the application of Bayes’ rule inadequate. Uniform or arbitrary priors may often provide classification answers that, even in simple examples, may end up contradicting our common sense about the problem. Entropic priors, via application of the maximum entropy principle, seem to provide a much better answer and can ...

In the framework of multicriteria decision making based on Choquet integrals, we present a maximum entropy like method enabling to determine, if it exists, the least specific capacity compatible with the initial preferences of the decision maker.

A method, which we suggest to call the Empirical Maximum Entropy method, is implicitly present at Maximum Entropy Empirical Likelihood method, as its special, non-parametric case. From this vantage point the entropy-based empirical approach to estimation is surveyed.

The game which can be taken to lie behind the maximum entropy principle is studied. Refining previous techniques, we present a comprehensive and satisfactory theoretical discussion of the fundamentals of this game in its simplest setting. The results are illustrated by concrete examples pertaining to well known classical models.

Based on the principle of maximum entropy the primary morphologic equation is derived, and then the equations for hydraulic geometry of longitudinal profile and crosssection are established. For V-shaped cross-sections the relevant morphologic equations which are derived are compared with the existing empirical and semi-empirical formulae. They show good agreement with the prototypes.

Analysis of speech acts and discourse structures is essential to a dialogue understanding system because speech acts and discourse structures are closely tied with the speaker’s intention. However, it has been difficult to infer a speech act and a discourse structure from a surface utterance because they highly depend on the context of the utterance. We propose a statistical dialogue analysis m...