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  • Ký hiệu PL/XG: 006.312 R7412
    Nhan đề: Data mining :
ISBN 9781498763974
DDC 006.312
Tác giả CN Roiger, Richard J.
Nhan đề Data mining : a tutorial-based primer / Richard J Roiger
Lần xuất bản 2nd ed.
Thông tin xuất bản Boca Raton : Chapman & Hall/CRC, 2017.
Mô tả vật lý 487 pages. : illustrations ; 25 cm.
Tùng thư Chapman & Hall/CRC data mining and knowledge discovery series
Tóm tắt "Dr. Roiger does an excellent job of describing in step by step detail formulae involved in various data mining algorithms, along with illustrations. In addition, his tutorials in Weka software provide excellent grounding for students in comprehending the underpinnings of Machine Learning as applied to Data Mining. The inclusion of RapidMiner software tutorials and examples in the book is also a definite plus since it is one of the most popular Data Mining software platforms in use today." --Robert Hughes, Golden Gate University, San Francisco, CA, USA Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a data mining solution is a feasible alternative for a specific problem. Fundamental data mining strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools. Several new topics have been added to the second edition including an introduction to Big Data and data analytics, ROC curves, Pareto lift charts, methods for handling large-sized, streaming and imbalanced data, support vector machines, and extended coverage of textual data mining. The second edition contains tutorials for attribute selection, dealing with imbalanced data, outlier analysis, time series analysis, mining textual data, and more. The text provides in-depth coverage of RapidMiner Studio and Weka's Explorer interface. Both software tools are used for stepping students through the tutorials depicting the knowledge discovery process. This allows the reader maximum flexibility for their hands-on data mining experience.
Thuật ngữ chủ đề Data mining
Thuật ngữ chủ đề Computer programming
Thuật ngữ chủ đề Database management
Khoa Khoa Công nghệ Thông tin
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100 |aRoiger, Richard J.
245 |aData mining : |ba tutorial-based primer / |cRichard J Roiger
250 |a2nd ed.
260 |aBoca Raton : |bChapman & Hall/CRC, |c2017.
300 |a487 pages. : |billustrations ; |c25 cm.
490 |aChapman & Hall/CRC data mining and knowledge discovery series
504 |aIncludes bibliographical references (pages 461-464) and index.
520 |a"Dr. Roiger does an excellent job of describing in step by step detail formulae involved in various data mining algorithms, along with illustrations. In addition, his tutorials in Weka software provide excellent grounding for students in comprehending the underpinnings of Machine Learning as applied to Data Mining. The inclusion of RapidMiner software tutorials and examples in the book is also a definite plus since it is one of the most popular Data Mining software platforms in use today." --Robert Hughes, Golden Gate University, San Francisco, CA, USA Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a data mining solution is a feasible alternative for a specific problem. Fundamental data mining strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools. Several new topics have been added to the second edition including an introduction to Big Data and data analytics, ROC curves, Pareto lift charts, methods for handling large-sized, streaming and imbalanced data, support vector machines, and extended coverage of textual data mining. The second edition contains tutorials for attribute selection, dealing with imbalanced data, outlier analysis, time series analysis, mining textual data, and more. The text provides in-depth coverage of RapidMiner Studio and Weka's Explorer interface. Both software tools are used for stepping students through the tutorials depicting the knowledge discovery process. This allows the reader maximum flexibility for their hands-on data mining experience.
541 |aMua
650 |aData mining
650 |aComputer programming
650 |aDatabase management
690 |aKhoa Công nghệ Thông tin
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