Feature Engineering and Selection - A Practical Approach for Predictive Models

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.

Summary

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.

Product details

• Authors: Kjell Johnson, Johnson Kjell, Max Kuhn, Max Johnson Kuhn, Kuhn Max
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.06.2021
• EAN: 9781032090856
• ISBN: 978-1-0-3209085-6
• No. of pages: 314
• Series: Chapman & Hall/CRC Data Science Series
• Subjects: Natural sciences, medicine, IT, technology > Biology > Ecology; Data Mining, Business & Economics / General, BUSINESS & ECONOMICS / Statistics, MATHEMATICS / Probability & Statistics / General, COMPUTERS / Machine Theory, computer science, Probability & statistics, Automatic control engineering, Databases, Probability and statistics, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Data Science / Data Analytics