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The field of Data Mining is widely recognized and accepted for its applications in many business problems to guide decision-making processes based on data. However, in recent times, the scope

The field of Data Mining is widely recognized and accepted for its applications in many business problems to guide decision-making processes based on data. However, in recent times, the scope of these problems has swollen and the methods are under scrutiny for applicability and relevance to real-world circumstances. At the crossroads of innovation and standards, it is important to examine and understand whether the current theoretical methods for industrial applications (which include KDD, SEMMA and CRISP-DM) encompass all possible scenarios that could arise in practical situations.

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    Date Created
    • 2012
    Resource Type
  • Text
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    Note
    • Partial requirement for: M.S., Arizona State University, 2012
      Note type
      thesis
    • Includes bibliographical references (p. 58-59)
      Note type
      bibliography
    • Field of study: Computer science

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    by Aneeth Anand

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