Supervised Descriptive Rule Induction

Petra  Kralj Novak; Nada Lavrač; Geoffrey I. Webb

doi:10.1007/978-0-387-30164-8_802

Supervised Descriptive Rule Induction

Petra Kralj Novak, Nada Lavrač, Geoffrey I. Webb

Department of Network and Data Science

Research output: Contribution to Book/Report types › Entry for encyclopedia/dictionary › peer-review

Abstract (may include machine translation)

Supervised descriptive rule induction (SDRI) is a machine learning task in which individual patterns in the form of rules (see Classification rule) intended for interpretation are induced from data, labeled by a predefined property of interest. In contrast to standard supervised rule induction, which aims at learning a set of rules defining a classification/prediction model, the goal of SDRI is to induce individual descriptive patterns. In this respect SDRI is similar to association rule discovery, but the consequents of the rules are restricted to a single variable – the property of interest – and, except for the discrete target attribute, the data is not necessarily assumed to be discrete.

Original language	English
Title of host publication	Encyclopedia of Machine Learning and Data Mining
Editors	Claude Sammut, Geoffrey I. Webb
Publisher	Springer New York
Pages	938–941
Number of pages	4
ISBN (Electronic)	978-0-387-30164-8
ISBN (Print)	978-0-387-30768-8
DOIs	https://doi.org/10.1007/978-0-387-30164-8_802
State	Published - 2010

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10.1007/978-0-387-30164-8_802

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abstract = "Supervised descriptive rule induction (SDRI) is a machine learning task in which individual patterns in the form of rules (see Classification rule) intended for interpretation are induced from data, labeled by a predefined property of interest. In contrast to standard supervised rule induction, which aims at learning a set of rules defining a classification/prediction model, the goal of SDRI is to induce individual descriptive patterns. In this respect SDRI is similar to association rule discovery, but the consequents of the rules are restricted to a single variable – the property of interest – and, except for the discrete target attribute, the data is not necessarily assumed to be discrete.",

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Supervised Descriptive Rule Induction

Abstract (may include machine translation)

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