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By Claude Sammut, Geoffrey I. Webb

This complete encyclopedia, with over 250 entries in an A-Z layout, offers easy accessibility to correct info for these looking access into any element in the large box of laptop studying. so much entries during this preeminent paintings comprise necessary literature references.

Topics for the Encyclopedia of computer Learning have been chosen by way of a uncommon foreign advisory board. those peer-reviewed, highly-structured entries comprise definitions, illustrations, purposes, bibliographies and hyperlinks to comparable literature, offering the reader with a portal to extra distinct details on any given topic.

The variety of the entries within the Encyclopedia of computing device Learning is expository and educational, making the publication a realistic source for computer studying specialists, in addition to pros in different fields who have to entry this important info yet would possibly not have the time to paintings their manner via a complete textual content on their subject of interest.

The authoritative reference is released either in print and on-line. The print book contains an index of matters and authors. the net version supplementations this index with links in addition to inner links to similar entries within the textual content, CrossRef citations, and hyperlinks to extra major research.

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Extra resources for Encyclopedia of Machine Learning

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T ′ ⊭A father(john, steve), as this has no possible abductive explanations. Hence, despite the fact that the background theory is incomplete (in its abducible predicates), ACL can find an appropriate solution to the learning problem by suitably extending the background theory with abducible assumptions. Note that the learned theory without the integrity constraint would not satisfy the definition of ACL, because there would exist an abductive explanation for the negative example father(kathy, ellen), namely ∆− = {male(kathy)}.

New Generation Computing, , –. , & Bryant, C. (). Theory completion using inverse entailment. In Proceedings of the tenth international workshop on inductive logic programming (ILP-) (pp. –). Berlin: Springer. , & Mooney, R. J. (). Theory refinement combining analytical and empirical methods. Artificial Intelligence, , –. , & Sergot, M. (). Inference of gene relations from microarray data by abduction. In Proceedings of the eighth international conference on logic programming and non-monotonic reasoning (LPNMR’) (Vol.

Active learning is often used in settings where obtaining labeled data is expensive or time-consuming; by sequentially identifying which examples are most likely to be useful, an active learner can sometimes achieve good performance, using far less training data than would otherwise be required. Structure of Learning System In many machine learning problems, the training data are treated as a fixed and given part of the problem definition. In practice, however, the training data are often not fixed beforehand.

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