Feature Engineering and Selection: A Practical Approach for Predictive Models (Chapman & Hall/CRC Data Science Series)
ISBN-13:
9781138079229
ISBN-10:
1138079227
Edition:
1
Author:
Max Kuhn, Kjell Johnson
Publication date:
2019
Publisher:
Chapman and Hall/CRC
Format:
Hardcover
314 pages
Category:
Environmental Economics
,
Economics
,
Statistics
,
Education & Reference
,
Data Mining
,
Databases & Big Data
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Book details
ISBN-13:
9781138079229
ISBN-10:
1138079227
Edition:
1
Author:
Max Kuhn, Kjell Johnson
Publication date:
2019
Publisher:
Chapman and Hall/CRC
Format:
Hardcover
314 pages
Category:
Environmental Economics
,
Economics
,
Statistics
,
Education & Reference
,
Data Mining
,
Databases & Big Data
Summary
Feature Engineering and Selection: A Practical Approach for Predictive Models (Chapman & Hall/CRC Data Science Series) (ISBN-13: 9781138079229 and ISBN-10: 1138079227), written by authors
Max Kuhn, Kjell Johnson, was published by Chapman and Hall/CRC in 2019.
With an overall rating of 3.7 stars, it's a notable title among other
Environmental Economics
(Economics, Statistics, Education & Reference, Data Mining, Databases & Big Data) books. You can easily purchase or rent Feature Engineering and Selection: A Practical Approach for Predictive Models (Chapman & Hall/CRC Data Science Series) (Hardcover, Used) from BooksRun,
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Environmental Economics
books
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Description
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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