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Statistical Learning with Sparsity The Lasso and Generalizations by

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Published by CRC Press .
Written in English


Book details:

The Physical Object
FormatHardcover
ID Numbers
Open LibraryOL27305984M
ISBN 109781498712163

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  Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlCited by: Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of d A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is /5(23). Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a .   Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.

Statistical Learning with Sparsity. The Lasso and Generalizations | Trevor Hastie, Robert Tibshirani, Martin Wainwright | download | B–OK. Download books for free. Find books. Stanford University. Statistical Learning with Sparsity: The Lasso and Generalizations During the past decade there 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 provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable.

Statistical Learning with Sparsity: The Lasso and Generalizations - Ebook written by Trevor Hastie, Robert Tibshirani, Martin Wainwright. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Statistical Learning with Sparsity: The Lasso and Generalizations. Statistical Learning with Sparsity. DOI link for Statistical Learning with Sparsity. DOI link for Statistical Learning with Sparsity. Statistical Learning with Sparsity book. The Lasso and Generalizations. By Trevor Hastie, Robert Tibshirani, Martin Wainwright. Edition 1st Edition. First Published eBook Published 7 May Pub. Get this from a library! Statistical learning with sparsity: the lasso and generalizations. [Trevor Hastie; Robert Tibshirani; Martin Wainwright] -- This book presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear.   As a data scientist, I have a handful of books that serve as important resources for my work in the field – “Statistical Learning with Sparsity – The Lasso and Generalizations” by Trevor Hastie, Robert Tibshirani, and Martin Wainwright is one of them. This book earned a prominent position on my desk for a number of reasons.