JSM 2004 - Toronto

Abstract #300627

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Activity Number: 121
Type: Contributed
Date/Time: Monday, August 9, 2004 : 12:00 PM to 1:50 PM
Sponsor: Section on Statistical Computing
Abstract - #300627
Title: Data-mining From Different Perspectives
Author(s): Morteza Marzjarani*+
Companies: Saginaw Valley State University
Address: 7400 Bay Road, University Center, MI, 48710,
Keywords: databases ; statistics ; machine learning
Abstract:

Data-mining is a very powerful tool today in data analysis. Fast and easy access to large datasets allows researchers to use large datasets looking for hidden patterns, and use these patterns for making more accurate decisions or predictions. Data-mining can be viewed from several perspectives. Here, we would like to consider three of such perspectives: the machine learning perspective, the database perspective, and the statistical perspective. In each perspective the emphasis is different. In case of database, since mining is applied to large datasets, efficiency is a major concern. In case of machine learning, datasets are not necessarily large, but effectiveness is an important issue. Finally, in case of data mining from statistical perspective, validity or accuracy of the mathematical models is of great concern.

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Revised March 2004