Data Mining for Business Analytics: Concepts, Techniques, and Applications in R (Hardcover)

Galit Shmueli, Peter C Bruce, Inbal Yahav, Nitin R Patel, Kenneth C Lichtendahl Jr.

  • 出版商: Wiley
  • 出版日期: 2017-09-05
  • 售價: $4,420
  • 貴賓價: 9.5$4,199
  • 語言: 英文
  • 頁數: 574
  • 裝訂: Hardcover
  • ISBN: 1118879368
  • ISBN-13: 9781118879368
  • 相關分類: R 語言Data-mining
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商品描述

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration

Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities.

This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes:

• Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government

• Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students

• More than a dozen case studies demonstrating applications for the data mining techniques described

• End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented

• A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

“ This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.”

Gareth M. James,  University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 publications including books.

Peter C. Bruce is President and Founder of the Institute for Statistics Education at Statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective (Wiley) and co-author of Practical Statistics for Data Scientists: 50 Essential Concepts (O’Reilly).

Inbal Yahav, PhD, is Professor at the Graduate School of Business Administration at Bar-Ilan University, Israel. She teaches courses in social network analysis, advanced research methods, and software quality assurance. Dr. Yahav received her PhD in Operations Research and Data Mining from the University of Maryland, College Park.

Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad, for 15 years.

Kenneth C. Lichtendahl, Jr., PhD, is Associate Professor at the University of Virginia. He is the Eleanor F. and Phillip G. Rust Professor of Business Administration and teaches MBA courses in decision analysis, data analysis and optimization, and managerial quantitative analysis. He also teaches executive education courses in strategic analysis and decision-making, and managing the corporate aviation function.

商品描述(中文翻譯)

《商業分析的資料探勘:概念、技術和R應用》以應用的方式介紹了資料探勘的概念和方法,並使用R軟體進行示範。

讀者將學習如何在R(一款免費且開源的軟體)中實施各種流行的資料探勘演算法,以應對商業問題和機會。

這是該成功教材的第五版,也是首次使用R。它涵蓋了用於預測、分類、可視化、降維、推薦系統、聚類、文本探勘和網絡分析的統計和機器學習演算法。它還包括:

- 兩位新合著者Inbal Yahav和Casey Lichtendahl,他們在使用R教授商業分析課程和在商業和政府領域進行資料探勘咨詢方面具有專業知識和經驗。
- 根據MBA、本科、文憑和執行課程的教師以及學生的反饋進行的更新和新內容。
- 逾十個案例研究,展示了所描述的資料探勘技術的應用。
- 結束章節的練習,幫助讀者評估和擴展他們對所呈現材料的理解和能力。
- 附帶網站,提供超過二十個資料集以及教師資料,包括練習解答、PowerPoint幻燈片和案例解答。

《商業分析的資料探勘:概念、技術和R應用》是研究生和高年級本科課程中資料探勘、預測分析和商業分析的理想教科書。這本新版也是在商業、金融、市場營銷、計算機科學和信息技術領域使用量化方法的分析師、研究人員和從業人員的優秀參考資料。

“這本書對商業分析方法進行了最全面的評論,從經典方法如線性和邏輯回歸,到現代方法如神經網絡、裝袋和提升,甚至更多商業特定的程序,如社交網絡分析和文本探勘。如果不是聖經,至少也是這個領域的權威手冊。”
- Gareth M. James,南加州大學教授,與Witten、Hastie和Tibshirani合著暢銷書《統計學習導論:R應用》

Galit Shmueli博士是國立清華大學服務科學研究所的特聘教授。她自2004年以來在馬里蘭大學、Statistics.com、印度商學院和國立清華大學(台灣)設計和教授資料探勘課程。Shmueli教授以商業分析領域的研究和教學聞名,專注於信息系統和醫療保健領域的統計和資料探勘方法。她已經出版了70多篇論文,包括書籍。

Peter C. Bruce是統計學教育研究所Statistics.com的創始人和主席。他撰寫了多篇期刊文章,並開發了Resampling Stats軟體。他是《入門統計學和分析:重抽樣觀點》(Wiley)的作者,也是《資料科學家的實用統計學:50個基本概念》(O'Reilly)的合著者。

Inbal Yahav博士是以色列巴伊蘭大學商學管理研究生院的教授。她教授社交網絡分析、高級研究方法和軟體品質保證課程。Yahav博士在馬里蘭大學(College Park)獲得了運營研究和資料探勘的博士學位。

Nitin R. Patel博士是位於麻省劍橋的Cytel公司的主席和共同創始人。