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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Statistical Learning from a Regression Perspective

Statistical Learning from a Regression Perspective

Berk, Richard a.

Hardcover

Series: Springer Texts in Statistics

Medical ReferenceGeneral SociologyProbability & Statistics

ISBN10: 303040188X
ISBN13: 9783030401887
Publisher: Springer Nature
Published: Jun 30 2020
Pages: 433
Weight: 1.80
Height: 1.00 Width: 6.14 Depth: 9.21
Language: English

This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable, given a set of predictors, and in the absence of a credible model that can be specified before the data analysis begins. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis depends in an integrated fashion on sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. The unifying theme is that supervised learning properly can be seen as a form of regression analysis. Key concepts and procedures are illustrated with a large number of real applications and their associated code in R, with an eye toward practical implications. The growing integration of computer science and statistics is well represented including the occasional, but salient, tensions that result. Throughout, there are links to the big picture.

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