TY  - BOOK
AU  - Kuhn,Max
AU  - Johnson,Kjell
TI  - Feature engineering and selection: a practical approach for predictive models 
T2  - Chapman & Hall/CRC data science series
SN  - 1138079227
AV  - TJ217.6 .K84 2020
PY  - 2020///
CY  - Boca Raton : 
PB  - CRC Press, Taylor & Francis Group
KW  - Predictive control
KW  - Data processing
KW  - Mathematical models
KW  - R (Computer program language)
N1  - Includes bibliographical references and index; Illustrative example: predicting risk of ischemic stroke -- A review of the predictive modeling process -- Exploratory visualizations -- Encoding categorical predictors -- Engineering numeric predictors -- Detecting interaction effects -- Handling missing data -- Working with profile data -- Feature selection overview -- Greedy search methods -- Global search methods
N2  - 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 finding 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
ER  -