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    Dr Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S. degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests focus on the development of novel data mining algorithms for a broad range of applications, including climate and ecological sciences, cybersecurity

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    Dr Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S. degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests focus on the development of novel data mining algorithms for a broad range of applications, including climate and ecological sciences, cybersecurity

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  • Introduction to Data Mining (Second Edition)

    Introduction to Data Mining (Second Edition) Pang-Ning Tan, Michigan State University, Michael Steinbach, University of Minnesota Provides both theoretical and practical coverage of all data mining topics. Includes extensive number of integrated examples and figures.

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    Introduction to Data Mining. Tan et al. First Edition Introduction to Data Mining ISBN 978-1-29202-615-2 Tan Steinbach Kumar First Edition 9 781292 026152 Introduction to Data Mining Tan

  • Introduction to Data Mining (2nd Edition) (What's New in

    Dr Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S. degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests focus on the development of novel data mining

  • Reviews: 28
  • Tan, Steinbach, Karpatne & Kumar, Introduction to Data

    Dr Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S. degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests focus on the development of novel data mining

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    Jul 10, 2016· Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining

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  • (PDF) Introduction-to-Data-Mining.pdf 11140930000080

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  • Introduction to Data Mining Edition 1 by Pang-Ning Tan

    Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining

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  • Introduction to Data Mining Pang-Ning Tan, Michael

    Dr Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S. degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests focus on the development of novel data mining

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  • Introduction to Data Mining (First Edition)

    Introduction to Data Mining (First Edition) Pang-Ning Tan, Michigan State University, Michael Steinbach, University of Minnesota Vipin Kumar, University of Minnesota Table of Contents Sample

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    Tan, Pang-Ning, Steinbach, Michael, Kumar, Vipin "Introduction to Data Mining is a complete introduction to data mining for students, researchers, and professionals. It provides a sound understanding of the foundations of data mining

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    Instructor Solutions Manual for Introduction to Data Mining. Pang-Ning Tan, Michigan State University. Michael Steinbach, University of Minnesota

  • (PDF) Introduction-to-Data-Mining.pdf 11140930000080

    Academia.edu is a platform for academics to share research papers.

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    Introduction to Data Mining, 2nd Edition Pearson Pang-Ning Tan, Michael Steinbach, and Vipin Kumar, "Introduction to Data Mining", Pearson Addison Wesley, 2008, ISBN: 0-32-134136-7.

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