Learning Taxonomic Relation by Case-based Reasoning
Author: Ken Satoh.
Source: Lecture Notes in Artificial Intelligence Vol. 1968, 2000, 179 - 193.
Abstract. In this paper, we propose a learning method of minimal casebase to represent taxonomic relation in a tree-structured concept hierarchy. We firstly propose case-based taxonomic reasoning and show an upper bound of necessary positive cases and negative cases to represent a relation. Then, we give an learning method of a minimal casebase with sampling and membership queries. We analyze this learning method by sample complexity and query complexity in the framework of PAC learning.
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