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Rough Set Theory in the Classification of Diagnoses
Ansvarlig organisasjon
2007 (engelsk)Konferansepaper, Oral presentation only (Fagfellevurdert) Published
Abstract [en]

Rough sets, surrounded by two approximation sets filled with sure and possible members constitute perfect mathematical tools of the classification of some objects. In this work we adopt the rough technique to verify diagnostic decisions concerning a sample of patients whose symptoms are typical of a considered diagnosis. The objective is to extract the patients who surely suffer from the diagnosis, to indicate the patients who are free from it, and even to make decisions in undefined diagnostic cases. By applying selected logical decision rules, we also discuss a possibility of reducing of symptom sets to their minimal collections preserving the previous results in order to minimize a number of numerical calculations.

sted, utgiver, år, opplag, sider
Lodz, Poland: The College of Computers Science , 2007.
Emneord [en]
Rough sets, lower and upper approximation, classification, reducts as minimal sets of conditional attributes
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Identifikatorer
URN: urn:nbn:se:bth-8889Lokal ID: oai:bth.se:forskinfoD40F71B7BE21B3A6C12573640062A139ISBN: 978-83-60282-03-8 (tryckt)OAI: oai:DiVA.org:bth-8889DiVA, id: diva2:836660
Konferanse
Computers in Medical Activity
Tilgjengelig fra: 2012-09-18 Laget: 2007-09-28 Sist oppdatert: 2016-09-20bibliografisk kontrollert

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Rakus-Andersson, Elisabeth

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Totalt: 47 treff
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