Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/114
Title: An Analytical Review of Data Mining Tools
Authors: Igiri, Chinwe Peace
Keywords: —Classification, Clustering, Data mining; Open sourc
Issue Date: Apr-2015
Publisher: International Journal of Engineering Research & Technology
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
Series/Report no.: 4;4
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
URI: http://localhost:8080/xmlui/handle/123456789/114
ISSN: 2278-0181
Appears in Collections:Computer Science

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