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Download Machine Learning Proceedings 1988. Proceedings of the Fifth by John Laird PDF

By John Laird

Court cases of June 1988. unique articles specialize in many parts of desktop studying together with empirical tools, explanation-based equipment, genetic algorithms, connectionist studying, probabilistic tools and formal theories of studying. No index. Annotation copyright e-book information, Inc. Portland, Or

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Read Online or Download Machine Learning Proceedings 1988. Proceedings of the Fifth International Conference on Machine Learning, June 12–14, 1988, University of Michigan, Ann Arbor PDF

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Additional resources for Machine Learning Proceedings 1988. Proceedings of the Fifth International Conference on Machine Learning, June 12–14, 1988, University of Michigan, Ann Arbor

Example text

Unate functions are those which can be created from elementary propositions using conjunction and disjunction only, without negation. For example, the expression a'b'c v a'd is unate. The expression a'b v ab is non-unate because a appears both negated and non-negated Criteria tables are naturally unate because they list findings only once. A finding may include negation (such as "no fever") but the non-negated finding (such as "fever") would then not be listed because it would not be characteristic of the disease concept described by the criteria table.

T h e first s t e p map(H,M) finds an initial m a p p i n g T, by assigning leaves of M t o leaves of H, Learning Graph Models of Shape based on similarity of their contexts. A context of a leaf v is the set of relations in which v participates. It is described by a support set SPS(v). SPS(v) is a set of pairs {(K,R)}, where K describes a relation by its label and the position of v in its argument list, and R describes the occurrences of K among ancestors of v. For a leaf of H, R is the number of times K repeats among its ancestors.

For a leaf of H, R is the number of times K repeats among its ancestors. For a leaf of M, R is a list containing \og[p(l,u)/p(l)} for each occurrence of K in an ancestor u, sorted in a decreasing order. '|) 5J i=0 , Ä·' (K,R)esps(v) where equal returns 1 or 0. S(u,v) is the upper bound on the contribution of an assignment (u,v) to Q. Map finds the pair of most similar leaves and removes them from leaf sets, then it finds a pair of most similar leaves in the remaining leaf sets, and so on, until the smaller set is exhausted.

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