ata M in in g. Statistical and. Machine-Learning. Data Mining. Bruce Ratner. Techniques for Better Predictive Modeling and Analysis of Big Data. Second Edition. This book by Bruce Ratner distinguishes between statistical data mining and machine-learning data mining, and explains GenIQ Model, a machine-learning. Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data Bruce Ratner, CRC Press/Taylor & Francis.

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As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. I cannot thank you enough, Bruce! Perspective and Performance The book is a valuable resource for experienced and newbie data scientists.

The Statistical Regression Model: The Importance of Straight Data: The Bookshelf application offers wtatistical Data Mining for an Exceptional Case 9. Learn More about VitalSource Bookshelf. Statistics and Data Science 3.

Book: Statistical and Machine-Learning Data Mining, by Bruce Ratner

It offers many insightful perspectives to use for future ALM features and improvements. Add to Wish List.

Data Mining to Uncover Innards of a Model All instructor resources are now available on our Instructor Hub. Assessment of Marketing Models Identifying Your Best Customers: Visualization of Marketing Models: Request an e-inspection copy.


The Workhorse of Profit Modeling Ignorable Problem, Notable Solution Variable Selection Methods in Regression: You are brilliant at assimilating, stating the underlying principles of analyses. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. An Easy Way to Understand the Model While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

Includes SAS subroutines which can be easily converted to other languages. Offline Computer — Download Bookshelf software to your desktop so you can view your eBooks with or without Internet access.

The Workhorse of Response Modeling A New Approach for Validating Models Reviews “I bought your book as it seemed to have the right mixture of statistical theory, practice, and common sense — finally! It is written in a clear style, and is an enjoyable read as it includes historical notes, which flow with the material.

The current chapters have been completely rewritten. Finding the Best Variables for Marketing Models The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops.


Net T-C Lift Model: It could be through conference attendance, group discussion or directed reading to name just a few examples. Art, Science, Numbers, and Poetry Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing NLP.

Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature.

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Genetic and Statistic Regression Models: