Data mining – A review
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...
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sg-smu-ink.sis_research-105462024-11-15T06:54:03Z Data mining – A review LEE, S.J. SIAU, Keng 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. 1998-11-24T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/9546 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems |
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Databases and Information Systems LEE, S.J. SIAU, Keng Data mining – A review |
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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. |
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LEE, S.J. SIAU, Keng |
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LEE, S.J. SIAU, Keng |
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LEE, S.J. |
title |
Data mining – A review |
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Data mining – A review |
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Data mining – A review |
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Data mining – A review |
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Data mining – A review |
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data mining – a review |
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Institutional Knowledge at Singapore Management University |
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1998 |
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https://ink.library.smu.edu.sg/sis_research/9546 |
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