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     Research Journal of Applied Sciences, Engineering and Technology


A Study of Open Source Data Mining Tools and its Applications

P. Subathra, R. Deepika, K. Yamini, P. Arunprasad and Shriram K. Vasudevan
Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham (University), Coimbatore, India
Research Journal of Applied Sciences, Engineering and Technology  2015  10:1108-1132
http://dx.doi.org/10.19026/rjaset.10.1880  |  © The Author(s) 2015
Received: January ‎31, ‎2015  |  Accepted: March ‎12, ‎2015  |  Published: August 05, 2015

Abstract

Data Mining is a technology that is used for the process of analyzing and summarizing useful information from different perspectives of data. The importance of choosing data mining software tools for the developing applications using mining algorithms has led to the analysis of the commercially available open source data mining tools. The study discusses about the following likeness of the data mining tools-KNIME, WEKA, ORANGE, R Tool and Rapid Miner. The Historical Development and state-of-art; (i) The Applications supported, (ii) Data mining algorithms are supported by each tool, (iii) The pre-requisites and the procedures to install a tool, (iv) The input file format supported by each tool. To extract useful information from these data effectively and efficiently, data mining tools are used. The availability of many open source data mining tools, there is an increasing challenge in deciding upon the apace-updated tools for a given application. This study has provided a brief study about the open source knowledge discovery tools with their installation process, algorithms support and input file formats support.

Keywords:

Data mining , KNIME, ORANGE , Rapid Miner , R-tool , WEKA,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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