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.
Highlights
In the present era, the value and the explosive rate of data in the database and data repository storage seems to be increasing which has made the humans impossible to manually analyze them for valuable decision-making
At this period of time, there is an measurable amount of data mining tools available in the market such as, Konstanz Information Miner (KNIME) (“About Knime”, https://www.knime.org/), R-Tool (Spector, 2004), Waikato Environment for Knowledge Analysis (WEKA) (Hall et al, 2009) ORANGE and Rapid Miner etc., each of it has its set of own methods and algorithms that will be useful for effective and efficient extraction and utilization of meaningful data from the Data Warehouse (Wahbeh et al, 2011) and making it easy for the users in the knowledge gaining process
This comparative study will make things easier for a beginner to understand the usage of the data mining tools and to decide upon which tool can be used for the process
Summary
The value and the explosive rate of data in the database and data repository storage seems to be increasing which has made the humans impossible to manually analyze them for valuable decision-making. Data Mining plays an active part in the discovery of strategic patterns which is used to find relationship among the data using various data analytics tools by applying various statistical and mathematical concepts (Rangra and Bansal, 2014) At this period of time, there is an measurable amount of data mining tools available in the market such as, KNIME (“About Knime”, https://www.knime.org/), R-Tool (Spector, 2004), WEKA (Hall et al, 2009) ORANGE and Rapid Miner etc., each of it has its set of own methods and algorithms that will be useful for effective and efficient extraction and utilization of meaningful data from the Data Warehouse (storage of historical data) (Wahbeh et al, 2011) and making it easy for the users in the knowledge gaining process. A basic evaluation of these various tools are done and their installation procedures, supported algorithms for clustering and classification processes are been tabulated along with their supported input file formats
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