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Statistical Learning with Sparsity

The Lasso and Generalizations

Hodnocení knihy

Parametry

  • 367 stránek
  • 13 hodin čtení

Více o knize

Focusing on the challenges posed by big data, this book explores how the sparsity assumption can help extract meaningful patterns from extensive datasets, even when the number of features exceeds observations. It delves into various techniques, including the lasso for linear regression, generalized penalties, and numerical optimization methods. Additionally, it covers statistical inference for lasso models, sparse multivariate analysis, graphical models, and compressed sensing, providing a comprehensive guide to modern data analysis techniques.

Nákup knihy

Statistical Learning with Sparsity, Martin Wainwright, Robert Tibshirani, Trevor Hastie

Jazyk
Rok vydání
2015
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Doručení

Platební metody

4,3
Velmi dobrá
33 Hodnocení

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Titul
Statistical Learning with Sparsity
Podtitul
The Lasso and Generalizations
Jazyk
anglicky
Rok vydání
2015
Vazba
pevná
Počet stran
367
ISBN13
9781498712163
Série
Hodnocení
4,25 z 5
Anotace
Focusing on the challenges posed by big data, this book explores how the sparsity assumption can help extract meaningful patterns from extensive datasets, even when the number of features exceeds observations. It delves into various techniques, including the lasso for linear regression, generalized penalties, and numerical optimization methods. Additionally, it covers statistical inference for lasso models, sparse multivariate analysis, graphical models, and compressed sensing, providing a comprehensive guide to modern data analysis techniques.