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A01=Kjell Johnson
A01=Max Kuhn
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Author_Kjell Johnson
Author_Max Kuhn
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Category1=Non-Fiction
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Language_English
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Feature Engineering and Selection: A Practical Approach for Predictive Models

English

By (author): Kjell Johnson Max Kuhn

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.

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A01=Kjell JohnsonA01=Max KuhnAge Group_UncategorizedAuthor_Kjell JohnsonAuthor_Max Kuhnautomatic-updateCategory1=Non-FictionCategory=PBTCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=AvailablePrice_€50 to €100PS=Activesoftlaunch
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Product Details
  • Weight: 812g
  • Dimensions: 178 x 254mm
  • Publication Date: 02 Aug 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781138079229

About Kjell JohnsonMax Kuhn

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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