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2016-10-04
如果喜欢该文档,欢迎订阅【2017新书】文库,https://bbs.pinggu.org/forum.php?mod=collection&action=view&ctid=3238

图书名称:Data mining for business analytics : concepts, techniques, and applications in JMP Pro

作者:Bruce, Peter C.; Patel, Nitin Ratilal; Shmueli, Galit; Stephens, Mia L.

出版社:
John Wiley & Sons
页数:467
出版时间:2017
                          
语言:English

格式:pdf
内容简介:
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® presents an  applied and interactive approach to data mining.
Featuring hands-on applications with JMP Pro®, a statistical package from the SAS Institute, the book
uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting.
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® also includes:
  • Detailed summaries that supply an outline of key topics at the beginning of each chapter
  • End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material
  • Data-rich case studies to illustrate various applications of data mining techniques
  • A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field.

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2016-10-4 14:32:44
thanks for sharing
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2016-10-4 15:47:57
谢谢分享。
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2016-10-4 18:19:09
谢谢分享
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2016-10-4 18:26:28
Data mining for business analytics
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2016-10-4 21:23:18
感谢分享 节日快乐
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