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Description
  • There are various techniques for data mining and data analysis. Among them, hybrid approaches combining two or more algorithms gain importance as the complexity and dimension of real world data sets grows. In this paper, we present an application of evolutionary-fuzzy classification technique to data mining. Genetic programming is deployed to evolve a fuzzy classifier describing a set of anomalous patterns in data and the classifier is further used to prevent production of faulty products.
  • There are various techniques for data mining and data analysis. Among them, hybrid approaches combining two or more algorithms gain importance as the complexity and dimension of real world data sets grows. In this paper, we present an application of evolutionary-fuzzy classification technique to data mining. Genetic programming is deployed to evolve a fuzzy classifier describing a set of anomalous patterns in data and the classifier is further used to prevent production of faulty products. (en)
Title
  • Learning patterns from data by an evolutionary-fuzzy approach
  • Learning patterns from data by an evolutionary-fuzzy approach (en)
skos:prefLabel
  • Learning patterns from data by an evolutionary-fuzzy approach
  • Learning patterns from data by an evolutionary-fuzzy approach (en)
skos:notation
  • RIV/61989100:27240/11:86080817!RIV12-GA0-27240___
http://linked.open...avai/riv/aktivita
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  • P(GA102/09/1494)
http://linked.open...iv/cisloPeriodika
  • April
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  • 209132
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  • RIV/61989100:27240/11:86080817
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  • applications.; genetic programming; fuzzy classifiers; data mining (en)
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  • DE - Spolková republika Německo
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  • [00391DE48524]
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  • Advances in Soft Computing
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  • 87
http://linked.open...iv/tvurceVysledku
  • Krömer, Pavel
  • Platoš, Jan
  • Snášel, Václav
issn
  • 1615-3871
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-19644-7_14
http://localhost/t...ganizacniJednotka
  • 27240
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