A Fuzzy-logic Generalization of a Data Mining Approach.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F01%3A06010212" target="_blank" >RIV/67985807:_____/01:06010212 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

A Fuzzy-logic Generalization of a Data Mining Approach.

Original language description

Generalizations of statistical hypotheses testing to vague hypotheses have so far followed the most straightforward way - to replace the set defining the null hypothesis by a fuzzy set. In this paper, a principally different approach is proposed, based on the observational-logic. Its key idea is to view statistical testing of a fuzzy hypothesis as the application of an appropriate generalized quantifier of a fuzzy predicate calculus to predicates describing the data.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BA - General mathematics

OECD FORD branch

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Project

<a href="/en/project/IAA1030004" target="_blank" >IAA1030004: Mathematical foundations of inference under vagueness and uncertainty</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2001

Confidentiality

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

Name of the periodical

Neural Network World

ISSN

1210-0552

e-ISSN

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Volume of the periodical

11

Issue of the periodical within the volume

6

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

14

Pages from-to

595-610

UT code for WoS article

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EID of the result in the Scopus database

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