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On Mining Rules that Involve Inequalities from Decision Table
Ansvarlig organisasjon
2008 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert) Published
Abstract [en]

We introduce the notion of generating decision rules that involve inequalities. While a conventional decision rule expresses the trivial equality relations between attributes and values from the same or different objects, inequality rules express the non-equivalent relationships between attributes and values. The problem of mining inequality rules is formulated as a process of mining equality rules from a compensatory decision table. In order to mine high-order inequality rules, one can transform the original decision table to a high-order compensatory decision table, in which each new entity is a pair of objects. Any standard data-mining algorithm can then be used. We theoretically analyze the complexity of proposed models based on their meta-level representation in cognitive informatics. Mining inequalities in decision table makes a complementary feature of a rule induction system, which may result in generating a small number of short rules for domains where attributes have large number of values, and when majority of them are correlated with the same decision class.

sted, utgiver, år, opplag, sider
Stanford University, CA, USA : IEEE CS Press , 2008.
Emneord [en]
Rough set, decision table, rule induction, inequality rules, knowledge representation
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-8391DOI: 10.1109/COGINF.2008.4639176Lokal ID: oai:bth.se:forskinfo55F416119B7E9A15C12574E3003680D2ISBN: 978-1-4244-2538-9 (tryckt)OAI: oai:DiVA.org:bth-8391DiVA, id: diva2:836106
Konferanse
Cognitive Informatics, 2008. ICCI 2008. 7th IEEE
Tilgjengelig fra: 2012-09-18 Laget: 2008-10-15 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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