Please use this identifier to cite or link to this item: http://repositorio.grial.eu/handle/grial/2500
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dc.contributor.authorMishra, A.-
dc.contributor.authorGupta, B. B.-
dc.contributor.authorPeraković, D.-
dc.contributor.authorGarcía-Peñalvo, F. J.-
dc.date.accessioned2022-01-30T08:38:14Z-
dc.date.available2022-01-30T08:38:14Z-
dc.date.issued2021-12-26-
dc.identifier.citationMishra, A., Gupta, B. B., Peraković, D., & García-Peñalvo, F. J. (2021). A Survey on Data mining classification approaches. In Z. Zhou, K. T. Chui, B. B. Gupta, A. M. T, & J. Zhang (Eds.), SysCom 2021. Smart Systems and Advanced Computing 2021. Proceedings of International Conference on Smart Systems and Advanced Computing, New Delhi, India (Virtual Mode), December 26-27, 2021. CEUR-WS.org. http://ceur-ws.org/Vol-3080en
dc.identifier.issn1613-0073-
dc.identifier.urihttp://repositorio.grial.eu/handle/grial/2500-
dc.description.abstractIn this review article, we discuss a number of different classification algorithms used in data mining for unique applications. There are various techniques to analyse the data for continuous and discrete values. Though,in our research paper, we discuss algorithm used for classification and applied for data mining. Basically classification is a technique for categorising data into discrete categories depending on limitations. The Genetic algorithm C4.5, the Naive Bayes algorithm, and others are examples of classification algorithms.en
dc.language.isoenen
dc.publisherCEUR-WS.orgen
dc.subjectBaggingen
dc.subjectNaive Bayesen
dc.subjectSVNen
dc.subjectRandom Foresten
dc.subjectData miningen
dc.titleA Survey on Data mining classification approachesen
dc.typeArticleen
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