Statistical Learning with Sparsity : The Lasso and Generalizations

In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. The authors cover the lasso for linear regression, generali

• | : Trevor Hastie, Robert Tibshirani, Martin Wainwright
• | Publisher: Taylor & Francis Ltd
• | Publication Date: Dec 18, 2020
• | Country of Publication: United Kingdom
• | Number of Pages: 367 pages
• | Language: Unknown
• | Binding: Paperback / softback
• | ISBN-10: 0367738333
• | ISBN-13: 9780367738334