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.
| ISBN: | 9781032090856 |
| Publication date: | 30th June 2021 |
| Author: | Max Kuhn, Kjell Johnson |
| Publisher: | Chapman & Hall/CRC an imprint of CRC Press |
| Format: | Paperback |
| Pagination: | 298 pages |
| Series: | Chapman & Hall/CRC Data Science Series |
| Genres: |
Machine learning Data science and analysis: general Data mining |
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.
Feature Engineering and Selection features in the following genres: Machine learning, Data science and analysis: general, Data mining
Paperback, Hardback, Ebook. £48.59, down from the £53.99 cover price. Not Available.
Feature Engineering and Selection was written by Max Kuhn, Kjell Johnson and published by Chapman & Hall/CRC an imprint of CRC Press
Feature Engineering and Selection has 298 pages
Yes it is part of Chapman & Hall/CRC Data Science Series series
£48.59, reduced from £53.99. Not Available.