A review of data mining techniques

• Main Authors: LEE, Sang Jun, SIAU, Keng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2001
• Subjects: Data mining; artificial intelligence; algorithms; decision trees; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9490; https://ink.library.smu.edu.sg/context/sis_research/article/10490/viewcontent/10_1108_02635570110365989_pv.pdf
• Institution: Singapore Management University

Terabytes of data are generated everyday in many organizations. To extract hidden predictive information from large volumes of data, data mining (DM) techniques are needed. Organizations are starting to realize the importance of data mining in their strategic planning and successful application of DM techniques can be an enormous payoff for the organizations. This paper discusses the requirements and challenges of DM, and describes major DM techniques such as statistics, artificial intelligence, decision tree approach, genetic algorithm, and visualization.