An Analytical Review of Data Mining Tools

Igiri, Chinwe Peace

dc.contributor.author	Igiri, Chinwe Peace
dc.date.accessioned	2022-06-17T12:50:43Z
dc.date.available	2022-06-17T12:50:43Z
dc.date.issued	2015-04
dc.identifier.citation	igiri, 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 04	en_US
dc.identifier.issn	2278-0181
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/114
dc.description.abstract	Data 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 commercial	en_US
dc.description.sponsorship	Igiri, Chinwe Peace	en_US
dc.language.iso	en	en_US
dc.publisher	International Journal of Engineering Research & Technology	en_US
dc.relation.ispartofseries	4;4
dc.subject	—Classification, Clustering, Data mining; Open sourc	en_US
dc.title	An Analytical Review of Data Mining Tools	en_US
dc.type	Article	en_US