Proceedings of the Eighth International Machine Learning Workshop, pp. 534-538, Evanston, IL, June 1991.
Paper ID: 6
Category: Theory and Knowledge Refinedment
This paper presents an approach to improving the classification performance of a multiple category theory by correcting intermediate rules which are shared among the categories. Using this technique, the performance of a theory in one category can be improved through training in an entirely different category. Examples of the technique are presented and experimental results are given.
