Application of boolean expression minimization to learning via hierarchical generalization
Document Type
Conference Proceeding
Publication Date
4-6-1994
Abstract
Concept learning through hierarchical generalization is an important technique in machine learning. The main result of this paper shows that this particular type of learning can be done using the well-known technique of boolean expression minimization. The boolean formulation unifies the various techniques suggested previously for hierarchical generalizations. It gives better conceptual clarity and a computationally efficient method for this type of learning. In particular, learning from relational databases can also be cast in the framework of boolean minimization.
Publication Source (Journal or Book title)
Proceedings of the ACM Symposium on Applied Computing
First Page
303
Last Page
307
Recommended Citation
Chen, J. (1994). Application of boolean expression minimization to learning via hierarchical generalization. Proceedings of the ACM Symposium on Applied Computing, Part F129433, 303-307. https://doi.org/10.1145/326619.326754