About: Mining multi-class industrial data with evolutionary fuzzy rules

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06617453
Description	Methods based on fuzzy sets and fuzzy logic have proved to be efficient data classifiers and value estimators. This study presents an application of evolutionary evolved fuzzy rules based on the concept of extended Boolean queries to a multiclass data mining problem. Fuzzy rules are used as symbolic classifiers machine-learned from the data and used to label data samples and predict the value of an output variable. The output variable can be both a label (category) and a continuous value. This study presents an application of evolutionary fuzzy rules to the prediction of multi-class quality attributes in an industrial data set and compares the prediction obtained by fuzzy rules to the prediction achieved by support vector machines. Methods based on fuzzy sets and fuzzy logic have proved to be efficient data classifiers and value estimators. This study presents an application of evolutionary evolved fuzzy rules based on the concept of extended Boolean queries to a multiclass data mining problem. Fuzzy rules are used as symbolic classifiers machine-learned from the data and used to label data samples and predict the value of an output variable. The output variable can be both a label (category) and a continuous value. This study presents an application of evolutionary fuzzy rules to the prediction of multi-class quality attributes in an industrial data set and compares the prediction obtained by fuzzy rules to the prediction achieved by support vector machines. (en)
Title	Mining multi-class industrial data with evolutionary fuzzy rules Mining multi-class industrial data with evolutionary fuzzy rules (en)
skos:prefLabel	Mining multi-class industrial data with evolutionary fuzzy rules Mining multi-class industrial data with evolutionary fuzzy rules (en)
skos:notation	RIV/61989100:27740/13:86088856!RIV14-MSM-27740___
http://linked.open...avai/predkladatel	IT4Innovations
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Snášel, Václav Platoš, Jan Krömer, Pavel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / IT4Innovations
http://linked.open...dnocenehoVysledku	88487
http://linked.open...ai/riv/idVysledku	RIV/61989100:27740/13:86088856
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Multi-class Data Mining; Industrial Applications; Genetic Programming; Fuzzy Rules; Fuzzy Information Retrieval (en)
http://linked.open.../riv/klicoveSlovo	Industrial Applications Genetic Programming Fuzzy Rules Fuzzy Information Retrieval Multi-class Data Mining
http://linked.open...ontrolniKodProRIV	[22BF5A97DE9E]
http://linked.open...v/mistoKonaniAkce	Lausanne
http://linked.open...i/riv/mistoVydani	Danvers
http://linked.open...i/riv/nazevZdroje	2013 IEEE International Conference on Cybernetics, CYBCONF 2013
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Bio-Inspired Methods: research, development and knowledge transfer IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Krömer, Pavel Platoš, Jan Snášel, Václav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-06-13 (xsd:date)
number of pages	6 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/CYBConf.2013.6617453
http://purl.org/ne...btex#hasPublisher	IEEE
https://schema.org/isbn	978-1-4673-6469-0
http://localhost/t...ganizacniJednotka	27740

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