TY - JFULL AU - S. Sarumathi and N. Shanthi and S. Vidhya and M. Sharmila PY - 2014/7/ TI - A Review: Comparative Study of Diverse Collection of Data Mining Tools T2 - International Journal of Computer and Information Engineering SP - 1027 EP - 1033 VL - 8 SN - 1307-6892 UR - https://publications.waset.org/pdf/9998957 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 90, 2014 N2 - There have been a lot of efforts and researches undertaken in developing efficient tools for performing several tasks in data mining. Due to the massive amount of information embedded in huge data warehouses maintained in several domains, the extraction of meaningful pattern is no longer feasible. This issue turns to be more obligatory for developing several tools in data mining. Furthermore the major aspire of data mining software is to build a resourceful predictive or descriptive model for handling large amount of information more efficiently and user friendly. Data mining mainly contracts with excessive collection of data that inflicts huge rigorous computational constraints. These out coming challenges lead to the emergence of powerful data mining technologies. In this survey a diverse collection of data mining tools are exemplified and also contrasted with the salient features and performance behavior of each tool. ER -