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Learning Comprehensible Theories from Structured Data

Ng, Kee Siong


This thesis is concerned with the problem of learning comprehensible theories from structured data and covers primarily classification and regression learning. The basic knowledge representation language is set around a polymorphically-typed, higher-order logic. The general setup is closely related to the learning from propositionalized knowledge and learning from interpretations settings in Inductive Logic Programming. Individuals (also called instances) are represented as terms in the logic....[Show more]

CollectionsOpen Access Theses
Date published: 2005-10
Type: Thesis (PhD)


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