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Filtering by: Creator Tanaree, D. D. Funding Body This work was supported in part by NSF grant number IRl-86-57316 (Presidential Young Investigator Award) . Resource Type Technical Report

Exploiting symmetry properties in the evaluation of inductive learning algorithms : an empirical domain-independent comparative study

Creator:

Almuallim, Hussein

Abstract:

Although numerous Boolean concept learning algorithms have been introduced in the literature, little is known about what categories of concepts are actually learned satisfactorily by most of these algorithms. Conventional comparison studies, which test various algorithms in some chosen domain, do not provide such information, since their conclusions are limited...

Resource Type:

Technical Report

Full Text:

. Ehrenfeucht and D. Haussler. Learning Decision Trees From Random Examples. Proceedings of the First Workshop

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Exploiting symmetry properties in the evaluation of inductive learning algorithms : an empirical domain-independent comparative study

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