[PDF.01yu] Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

[PDF.rv52] Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

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 | #267194 in Books |  CRC Press |  2015-05-07 | Original language:English | PDF # 1 |  9.30 x.90 x6.10l,.0 | File type: PDF | 367 pages

 | CRC Press

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||1 of 2 people found the following review helpful.| Excellent!|By boolpp|Very helpful!! Exactly what I need, how I wish I could have found it earlier.|6 of 8 people found the following review helpful.| Bet on sparsity approach in Machine Learning.|By Vladislavs Dovgalecs|This book is about bet on sparsity. In Machine Learning, there are plenty of approaches that might work on da| ||"The authors study and analyze methods using the sparsity property of some statistical models in order to recover the underlying signal in a dataset. They focus on the Lasso technique as an alternative to the standard least-squares method."|―Zentralblatt

Discover New Methods for Dealing with High-Dimensional Data

A 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 underlying signal in a set of data.

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