An Overview of Data Mining Techniques and Applications

R. Tamilselvi, S. Kalaiselvi

Abstract: Data mining may be defined as the science of extracting useful information from databases. It also called knowledge discovery. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future. In this paper overview of data mining, Types and Components of data mining algorithms have been discussed. Data mining tasks like Decision Trees, Association Rules, Clustering, Time-series and its related data mining algorithms have been included. The working style and the data required for the algorithms are explained. Each algorithm has its own set of merits and demerits. We have also incorporated the various application domains of Decision Trees and Clustering algorithms.

Keywords: Data mining Techniques, Data mining algorithms, Data mining applications

How to Cite?: R. Tamilselvi, S. Kalaiselvi, "An Overview of Data Mining Techniques and Applications", Volume 2 Issue 2, February 2013, International Journal of Science and Research (IJSR), Pages: 506-509, https://www.ijsr.net/getabstract.php?paperid=IJSROFF2013059, DOI: https://dx.doi.org/10.21275/IJSROFF2013059