Abstract

We have presented in this paper a learning system that is able to produce characteristic and discriminant versions of disjunctive target concepts. The algorithm is able to process all classes at once. It integrates several inductive learning methods: An ID3-based system (with several important improvements over the original ID3) and a generalization engine. The first way we approached integration was to use a switchbox mecanism that enabled us to quickly identify strong and weak points of each learning systems. The switchbox integration was also used to test plausible ways of fully merging the systems. When the limit of what could possibly be done was reached, we then went on integrating totally the learning systems. This required major changes in the systems themselves and was achieved by designing a powerful object-based representation formalism and implementing a common pattern-matcher …

Date

2005

Authors

Michel Manago, Jim Blythe

Source

Knowledge Representation and Organization in Machine Learning

Pages

211-230

Publisher

Springer Berlin Heidelberg