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Statistical and Machine-Learning Data Mining: - Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition (Paperback, 3rd edition)
Loot Price: R1,528
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Statistical and Machine-Learning Data Mining: - Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition (Paperback, 3rd edition)
Expected to ship within 10 - 15 working days
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Interest in predictive analytics of big data has grown
exponentially in the four years since the publication of
Statistical and Machine-Learning Data Mining: Techniques for Better
Predictive Modeling and Analysis of Big Data, Second Edition. In
the third edition of this bestseller, the author has completely
revised, reorganized, and repositioned the original chapters and
produced 13 new chapters of creative and useful machine-learning
data mining techniques. In sum, the 43 chapters of simple yet
insightful quantitative techniques make this book unique in the
field of data mining literature. What is new in the Third Edition:
The current chapters have been completely rewritten. The core
content has been extended with strategies and methods for problems
drawn from the top predictive analytics conference and statistical
modeling workshops. 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). Includes
SAS subroutines which can be easily converted to other languages.
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. The author addresses each methodology and
assigns its application to a specific type of problem. To better
ground readers, the book provides an in-depth discussion of the
basic methodologies of predictive modeling and analysis. 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.
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