Measures of Ruleset Quality for General Rules Extraction Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F09%3A00323363" target="_blank" >RIV/67985807:_____/09:00323363 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Measures of Ruleset Quality for General Rules Extraction Methods

Popis výsledku v původním jazyce

The paper deals with quality measures of whole sets of rules extracted from data, as a counterpart to more commonly used measures of individual rules. It sketches the typology of rules extraction methods and of their rulesets, and recalls that quality measures for whole sets of rules have been so far used only in the case of classification rulesets. Then three particular approaches to extending ruleset quality measures from classification to general rulesets are discussed. The paper also recalls the possibility to measure the dependence of classification rulesets on parameters of the classification method by means of ROC curves, and proposes a generalization of ROC curves to general rulesets. Finally, the approach is illustrated on rulesets extracted with four important rules extraction methods from the well-known iris data.

Název v anglickém jazyce

Measures of Ruleset Quality for General Rules Extraction Methods

Popis výsledku anglicky

The paper deals with quality measures of whole sets of rules extracted from data, as a counterpart to more commonly used measures of individual rules. It sketches the typology of rules extraction methods and of their rulesets, and recalls that quality measures for whole sets of rules have been so far used only in the case of classification rulesets. Then three particular approaches to extending ruleset quality measures from classification to general rulesets are discussed. The paper also recalls the possibility to measure the dependence of classification rulesets on parameters of the classification method by means of ROC curves, and proposes a generalization of ROC curves to general rulesets. Finally, the approach is illustrated on rulesets extracted with four important rules extraction methods from the well-known iris data.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA201%2F08%2F0802" target="_blank" >GA201/08/0802: Aplikace metod znalostního inženýrství při dobývání znalostí z databází</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Approximate Reasoning

ISSN

0888-613X

e-ISSN

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Svazek periodika

50

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

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Kód UT WoS článku

000267232200005

EID výsledku v databázi Scopus

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