The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification

A model of general domain knowledge would enable cases to be matched based on semantic rather than purely syntactic criteria.. Hence, a general domain model combined with CBR

4 Next, in the first chapter, we respond directly to the devil’s advocate, by experimentally testing whether a constrained set of evidence (i.e., a handful of known words and

In this work, since the primary goal of learning the models is to verify properties over the systems, we evaluate the learning algorithms by checking whether we can reliably

We build two algebraic structures, symmetric delta lenses and (con- sistency) maintainers, which comprise delta-based synchronization operations and laws they must satisfy. Lenses

Consequently, the aim of this module is to modify students’ representations of the act of learning and to understand key issues such as self-directed learning and its

The case base is enriched with the help of learned adaptation rules: given a source case, another source case closer to the target problem is generated thanks to such a rule..

rule; Occam’s razor; Learning best model granularity; On-line handwritten character recognition; Improved elastic matching; Learning optimal feature extraction interval; Modeling

Figure 8: The estimated average trajec- tory. The fixed effects provide an ordering of the biomarkers and the relative delay between them. The random effects characterize