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Statistical Learning from a Regression Perspective
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Statistical Learning as a Regression Problem
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Chapter 2
Regression Splines and Regression Smoothers
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Chapter 3
Classification and Regression Trees (CART)
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Chapter 4
Bagging
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Chapter 5
Random Forests
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Chapter 6
Boosting
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Chapter 7
Support Vector Machines
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Chapter 8
Broader Implications and a Bit of Craft Lore
Overall attention for this book and its chapters
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Mentioned by
twitter
2
X users
syllabi
1
institution with syllabi
Citations
dimensions_citation
155
Dimensions
Readers on
mendeley
632
Mendeley
Book overview
1. Statistical Learning as a Regression Problem
2. Regression Splines and Regression Smoothers
3. Classification and Regression Trees (CART)
4. Bagging
5. Random Forests
6. Boosting
7. Support Vector Machines
8. Broader Implications and a Bit of Craft Lore
Summary
X
Syllabi
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
1
syllabus from an institution on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
University of Washington-Seattle Campus
1
Economics