Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro (Hardcover)

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.

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 journal articles, books, textbooks, and book chapters, including Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition, also published by Wiley.

Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.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 and co-author of Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner ®, Third Edition, both published by Wiley.

Mia Stephens is Academic Ambassador at JMP®, a division of SAS Institute. Prior to joining SAS, she was an adjunct professor of statistics at the University of New Hampshire and a founding member of the North Haven Group LLC, a statistical training and consulting company. She is the co-author of three other books, including Visual Six Sigma: Making Data Analysis Lean, Second Edition, also published by Wiley.

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. He is co-author of Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition, also published by Wiley.

《商業分析的資料探勘：概念、技術和應用（附JMP Pro®）》提供了一種應用和互動的資料探勘方法。

本書使用SAS Institute的統計軟體JMP Pro®進行實際應用，通過引人入勝的實例建立了對關鍵資料探勘方法的理論和實踐理解，特別是用於分類和預測的預測模型。主題包括資料可視化、降維技術、聚類、線性和邏輯回歸、分類和回歸樹、判別分析、朴素貝葉斯、神經網絡、提升建模、集成模型和時間序列預測。

《商業分析的資料探勘：概念、技術和應用（附JMP Pro®）》還包括：

- 每章開頭提供主題概述的詳細摘要
- 結尾的例子和練習，讓讀者擴展對所呈現材料的理解
- 資料豐富的案例研究，以說明各種資料探勘技術的應用
- 附帶網站，提供超過兩打的資料集、練習和案例研究解答，以及教師幻燈片

《商業分析的資料探勘：概念、技術和應用（附JMP Pro®）》是高年級本科和研究生課程的優秀教科書，涵蓋資料探勘、預測分析和商業分析。本書還是從事管理、金融、市場營銷、信息技術、醫療保健、教育和其他資料豐富領域的數據科學家、分析師、研究人員和從業人員的獨一無二的資源。

Galit Shmueli, PhD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等地設計和教授資料探勘課程。Shmueli教授以商業分析的研究和教學聞名，專注於信息系統和醫療保健領域的統計和資料探勘方法。她撰寫了70多篇期刊文章、書籍、教科書和章節，包括同樣由Wiley出版的《商業分析的資料探勘：概念、技術和應用（附XLMiner®）》第三版。

Peter C. Bruce是統計教育研究所（www.statistics.com）的總裁和創始人。他撰寫了多篇期刊文章，並開發了Resampling Stats軟體。他是《入門統計和分析：重抽樣觀點》的作者，也是《商業分析的資料探勘：概念、技術和應用（附XLMiner®）》第三版的合著者，這兩本書都由Wiley出版。

Mia Stephens是SAS Institute旗下JMP®的學術大使。加入SAS之前，她曾在新罕布什爾大學擔任統計學兼職教授，並是North Haven Group LLC的創始成員，該公司是一家統計培訓和咨詢公司。她是另外三本書的合著者，包括同樣由Wiley出版的《視覺化六西格瑪：使數據分析精簡》第二版。

Nitin R. Patel, PhD是位於麻薩諸塞州劍橋市的Cytel公司的主席和共同創始人。作為美國統計協會的會士，Patel博士還曾擔任麻省理工學院和哈佛大學的客座教授。他是印度管理學院艾哈邁德巴德分校的教授，並在該校任教15年。他是《商業分析的資料探勘：概念、技術和應用（附XLMiner®）》第三版的合著者，這本書同樣由Wiley出版。