The Elements of Statistical Learning
Book by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie
"During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. ... Google Books
Originally published: 2001
Authors: Trevor Hastie, Robert Tibshirani, and Jerome H. Friedman
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This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.
Chapter 18 explores the “p ≫ N” problem, which is learning in high- dimensional feature spaces. These problems arise in many areas, in- cluding genomic and ...
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This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the ...
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Technically-oriented PDF Collection (Papers, Specs, Decks, Manuals, etc) - pdfs/The Elements of Statistical Learning - Data Mining, Inference and Prediction ...
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The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, ...
The elements of statistical learning : data mining, inference, and prediction / · 1. Introduction · 2. Overview of supervised learning · 3. Linear methods for ...
May 11, 2020 · This book is designed for researchers and students in a broad variety of fields: statistics, artificial intelligence, engineering, finance and ...
Nov 11, 2013 · The many topics include neural networks, support vector machines, classification trees and boosting - the first comprehensive treatment of ...
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics) by Hastie, Trevor; Tibshirani, Robert; ...
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