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OverviewFull Product DetailsAuthor: Bruce RatnerPublisher: Taylor & Francis Ltd Imprint: Chapman & Hall/CRC Edition: 3rd edition Weight: 0.453kg ISBN: 9780367573607ISBN 10: 0367573601 Pages: 690 Publication Date: 30 June 2020 Audience: College/higher education , General/trade , Tertiary & Higher Education , General Format: Paperback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviews"""I bought your book as it seemed to have the right mixture of statistical theory, practice, and common sense – finally! You can find the first often; the second occasionally; but the third, esp. in combination with the first two – never. I cannot thank you enough, Bruce! You are brilliant at assimilating, stating the underlying principles of analyses."" ~Sandra Hendren, Sr. Lecturer, Harvard ""Bruce Ratner’s recent 3rd edition of ""Statistical and Machine-Learning Data Mining"" is the best I’ve seen in my long career. It provides insightful methods for data mining, and innovative techniques for predictive analytics. The book is a valuable resource for experienced and newbie data scientists. Bruce’s book is my new data science bible. It is written in a clear style, and is an enjoyable read as it includes historical notes, which flow with the material."" ~Jack Theurer, President, G. Theurer Assoc. Inc. ""Your book has been very helpful when I was reviewing the manual for the Automatic Linear Modeling (ALM) in SPSS. It offers many insightful perspectives to use for future ALM features and improvements. This book is an excellent contribution to the literature of statistics, data mining, and machine learning. Thank you, Bruce."" ~Patrick Yan, PhD, Professor, Arizona State Univ. ""I heard one of my instructors in Coursera mention Bruce Ratner’s new book ""Statistical and Machine-Learning Data Mining"" during an online chat when he became tired of answering questions."" ~Mike Richardson, Head of Hardware, Smartfrog, Inc. ""I bought your book as it seemed to have the right mixture of statistical theory, practice, and common sense – finally! You can find the first often; the second occasionally; but the third, esp. in combination with the first two – never. I cannot thank you enough, Bruce! You are brilliant at assimilating, stating the underlying principles of analyses."" ~Sandra Hendren, Sr. Lecturer, Harvard ""Bruce Ratner’s recent 3rd edition of ""Statistical and Machine-Learning Data Mining"" is the best I’ve seen in my long career. It provides insightful methods for data mining, and innovative techniques for predictive analytics. The book is a valuable resource for experienced and newbie data scientists. Bruce’s book is my new data science bible. It is written in a clear style, and is an enjoyable read as it includes historical notes, which flow with the material."" ~Jack Theurer, President, G. Theurer Assoc. Inc. ""Your book has been very helpful when I was reviewing the manual for the Automatic Linear Modeling (ALM) in SPSS. It offers many insightful perspectives to use for future ALM features and improvements. This book is an excellent contribution to the literature of statistics, data mining, and machine learning. Thank you, Bruce."" ~Patrick Yan, PhD, Professor, Arizona State Univ. ""I heard one of my instructors in Coursera mention Bruce Ratner’s new book ""Statistical and Machine-Learning Data Mining"" during an online chat when he became tired of answering questions."" ~Mike Richardson, Head of Hardware, Smartfrog, Inc." I bought your book as it seemed to have the right mixture of statistical theory, practice, and common sense - finally! You can find the first often; the second occasionally; but the third, esp. in combination with the first two - never. I cannot thank you enough, Bruce! You are brilliant at assimilating, stating the underlying principles of analyses. ~Sandra Hendren, Sr. Lecturer, Harvard Bruce Ratner's recent 3rd edition of Statistical and Machine-Learning Data Mining is the best I've seen in my long career. It provides insightful methods for data mining, and innovative techniques for predictive analytics. The book is a valuable resource for experienced and newbie data scientists. Bruce's book is my new data science bible. It is written in a clear style, and is an enjoyable read as it includes historical notes, which flow with the material. ~Jack Theurer, President, G. Theurer Assoc. Inc. Your book has been very helpful when I was reviewing the manual for the Automatic Linear Modeling (ALM) in SPSS. It offers many insightful perspectives to use for future ALM features and improvements. This book is an excellent contribution to the literature of statistics, data mining, and machine learning. Thank you, Bruce. ~Patrick Yan, PhD, Professor, Arizona State Univ. I heard one of my instructors in Coursera mention Bruce Ratner's new book Statistical and Machine-Learning Data Mining during an online chat when he became tired of answering questions. ~Mike Richardson, Head of Hardware, Smartfrog, Inc. Author InformationBruce Ratner, The Significant StatisticianTM, is President and Founder of DM STAT-1 Consulting, the ensample for Statistical Modeling, Analysis and Data Mining, and Machine-learning Data Mining in the DM Space. DM STAT-1 specializes in all standard statistical techniques, and methods using machine-learning/statistics algorithms, such as its patented GenIQ Model, to achieve its clients' goals – across industries including Direct and Database Marketing, Banking, Insurance, Finance, Retail, Telecommunications, Healthcare, Pharmaceutical, Publication & Circulation, Mass & Direct Advertising, Catalog Marketing, e-Commerce, Web-mining, B2B, Human Capital Management, Risk Management, and Nonprofit Fundraising. Bruce holds a doctorate in mathematics and statistics, with a concentration in multivariate statistics and response model simulation. His research interests include developing hybrid-modeling techniques, which combine traditional statistics and machine learning methods. He holds a patent for a unique application in solving the two-group classification problem with genetic programming. Tab Content 6Author Website:Countries AvailableAll regions |