Feature Engineering and Selection: A Practical Approach for Predictive Models by Kuhn, Max

Feature Engineering and Selection: A Practical Approach for Predictive Models (Paperback) (ISBN-13: 9781032090856)

Vendor: Max Kuhn
Product type: Books
Format: Paperback
$59.95
$59.95
$59.95
Subtotal: $59.95
Feature Engineering and Selection: A Practical Approach for Predictive Models by Kuhn, Max

Feature Engineering and Selection: A Practical Approach for Predictive Models

$59.95
Feature Engineering and Selection: A Practical Approach for Predictive Models by Kuhn, Max

Feature Engineering and Selection: A Practical Approach for Predictive Models

$59.95
Format: Paperback
Description
Description
x

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.



Author: Max Kuhn, Kjell Johnson
ISBN-10: 1032090855
ISBN-13: 9781032090856
Publisher: CRC Press
Language: English
Published: 06/30/2021
Pages: 314
Format: Paperback
Weight: 1.60lbs
Size: 9.90h x 7.00w x 0.60d
By Max Kuhn
By Max Kuhn
x

Max Kuhn, Ph.D., is a software engineer at RStudio. He worked in 18 years in drug discovery and medical diagnostics applying predictive models to real data. He has authored numerous R packages for predictive modeling and machine learning.

Kjell Johnson, Ph.D., is the owner and founder of Stat Tenacity, a firm that provides statistical and predictive modeling consulting services. He has taught short courses on predictive modeling for the American Society for Quality, American Chemical Society, International Biometric Society, and for many corporations.

Kuhn and Johnson have also authored Applied Predictive Modeling, which is a comprehensive, practical guide to the process of building a predictive model. The text won the 2014 Technometrics Ziegel Prize for Outstanding Book.

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