This NRL NCARAI technical note (AIC-95-003) describes work with Salzberg's (1991) NGE. I recently implemented this algorithm and have run a few case studies. The purpose of this note is to publicize this implementation and note a curious result while using it. This implementation of NGE is available at under my WWW address (see above) indexed under software.

The nested generalized exemplar theory accomplishes learning by storing objects in Euclidean n-space, as hyperrectangles. Classification of new data is performed by computing their distance to the nearest “generalized exemplar” or hyperrectangle. This learningmethod allows the combination of the distancebased classificationwith the axis-parallel rectangle representation employed inmost of the r...

We solve the problem of extending Bird and Paterson’s generalized folds for nested datatypes and its dual to inductive and coinductive constructors of arbitrarily high ranks by appropriately generalizing Mendler-style (co)iteration. Characteristically to Mendler-style schemes of disciplined (co)recursion, the schemes we propose do not rest on notions like positivity or monotonicity of a constru...

This paper presents an empirical study about the Nested Context Language (NCL), which is a language developed to create multimedia documents and Interactive Digital TV (IDTV) applications for the Brazilian system. The goal was to obtain indicators of NCL usability in the generation of content for IDTV, since this language plays the role of interface language for users. Through data collected on...

In the paper we propose nonparametric approaches for elearning data. In particular we want to supply a measure of the relative exercises importance, to estimate the acquired Knowledge for each student and finally to personalize the e-learning platform. The methodology employed is based on a comparison between nonparametric statistics for kernel density classification and parametric models such ...

A generalized mover-stayer model is described for conditionally Markov processes under panel observation. Marginally the model represents a mixture of nested continuous-time Markov processes in which sub-models are defined by constraining some transition intensities to zero between two or more states of a full model. A Fisher scoring algorithm is described which facilitates maximum likelihood e...

Discrete choice models have played an important role in transportation modeling for the last 25 years. They are namely used to provide a detailed representation of the complex aspects of transportation demand, based on strong theoretical justiications. Moreover, several packages and tools are available to help practionners using these models for real applications, making discrete choice models ...

This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled using the Shannon entropy function, the resulting choice probabilities in the rational inattention model take the multinomial logit form. By exploiting convex-analytic properties of the discrete choice model, we show ...