Statistical and Machine-Learning Data Mining:: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition

3rd Edition

Bruce Ratner

Chapman and Hall/CRC
Published June 1, 2017
Reference - 662 Pages - 200 B/W Illustrations
ISBN 9781498797603 - CAT# K30454

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•One of only two books on big data on Intel's prestigous recommended reading list

•Provides step-by-step solutions to common problems facing data scientists, modelers, and marketers; other books typically provide outlined-solutions.

•Illustrations involve real problems, real data, and better solutions.

•uniquely introduces two new machine-learning methods specifically tailored to database assessment of optimal model performance.

•new edition will add latest methodologies as well as SAS coverage


The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. is a compilation of new and creative data mining techniques, which address the scaling-up of the framework of classical and modern statistical methodology, for predictive modeling and analysis of big data. SM-DM provides proper solutions to common problems facing the newly minted data scientist in the data mining discipline. Its presentation focuses on the needs of the data scientists (commonly known as statisticians, data miners and data analysts), delivering practical yet powerful, simple yet insightful quantitative techniques, most of which use the "old" statistical methodologies improved upon by the new machine learning influence.


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