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dc.contributor.authorIgiri, Chinwe Peace-
dc.date.accessioned2022-06-17T12:50:43Z-
dc.date.available2022-06-17T12:50:43Z-
dc.date.issued2015-04-
dc.identifier.citationigiri, C. P. (2015). An Analytical Review of Data Mining Tools. International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 IJERTV4IS040611 www.ijert.org (This work is licensed under a Creative Commons Attribution 4.0 International License.) Vol. 4 Issue 04en_US
dc.identifier.issn2278-0181-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/114-
dc.description.abstractData mining plays a vital role in contemporary society and the corporate world as a whole. This paper reviews a number of different data mining tools including Environment for Knowledge Analysis (WEKA), Konstanz Information Miner (KNIME), GhostMiner, R Analytical Tool To Learn Easily (Rattle), and RapidMiner. More often than not, young researchers face the challenge of making the choice of a data mining tool to carry out their research. An evaluation of the capabilities, attributes, as well as sources, has also been done in this paper. The strengths and weaknesses of these tools have also been explored. It was established herein, that Waikato Environment for Knowledge Analysis (WEKA), Konstanz Information Miner (KNIME), R Analytical Tool To Learn Easily (Rattle) and RapidMiner are open source data mining tools and are provided under the GNU GPL licenses while GhostMiner is commercialen_US
dc.description.sponsorshipIgiri, Chinwe Peaceen_US
dc.language.isoenen_US
dc.publisherInternational Journal of Engineering Research & Technologyen_US
dc.relation.ispartofseries4;4-
dc.subject—Classification, Clustering, Data mining; Open sourcen_US
dc.titleAn Analytical Review of Data Mining Toolsen_US
dc.typeArticleen_US
Appears in Collections:Computer Science

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