Statistical Learning with Sparsity: The Lasso and Generalizations
The explosion in computation and information technology has brought vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.
Tag(s): Mathematics Statistics
Publication date: 07 May 2015
ISBN-10: 1498712169
ISBN-13: 9781498712163
Paperback: 367 pages
Views: 7,401
Type: N/A
Publisher: n/a
License: n/a
Post time: 10 Apr 2016 12:00:00
Statistical Learning with Sparsity: The Lasso and Generalizations
The explosion in computation and information technology has brought vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.
Publication date: 07 May 2015
ISBN-10: 1498712169
ISBN-13: 9781498712163
Paperback: 367 pages
Views: 7,401
Document Type: N/A
Publisher: n/a
License: n/a
Post time: 10 Apr 2016 12:00:00
During the past decade has been an explosion in computation and information technology. With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.
Tweet
About The Author(s)
Trevor Hastie is The John A. Overdeck Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University.
Trevor Hastie is The John A. Overdeck Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University.
Robert Tibshirani is a Professor of Health Research and Policy, and Statistics at Stanford University.
Robert Tibshirani is a Professor of Health Research and Policy, and Statistics at Stanford University.
Martin Wainwright is a Professor in the Department of Electrical Engineering and Computer Sciences, Department of Statistics, University of California at Berkeley.
Martin Wainwright is a Professor in the Department of Electrical Engineering and Computer Sciences, Department of Statistics, University of California at Berkeley.