Use of Data mining Tools in Educational Data Mining
Free open source software like Keel, KNIME, RapidMiner, Weka, Tanagra, and Orange are explained and compared and the free open source and the proprietary data mining tool is compared.
Abstract
Data Mining is the task of discovering the knowledge from huge amount of data. Data Mining algorithms includes classification, clustering, association rules, regression, summarization, and anomaly detection. There are various proprietary as well as free open source data mining tools using which these algorithms can be applied on the given datasets and analyze the same. This paper compares the free open source and the proprietary data mining tool. Here free open source software like Keel, KNIME, RapidMiner, Weka, Tanagra, and Orange are explained and compared. Proprietary tools like SPSS, KXEN, Microsoft Analysis Services, SAS Enterprise Miner, STATISTICA, and Oracle Data Mining are also explained and compared on the basis of operating system, type, licenses, etc. Weka is mostly used tool for analyzing the data. Use of these data mining tools is elucidated with Name of tool, Data Mining Techniques applied, Algorithm used, Performance parameter considered and Dataset used in Educational Data Mining (EDM).