The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition

Machine Learning Published 2016 12991.8 KB ✓ Verified Direct PDF

Overview & Synopsis

This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting - the first comprehensive treatment of this topic in any book.

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Document Information

Document Title The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition
Author / Organization Trevor Hastie, Robert Tibshirani, Jerome Friedman
Subject & Discipline Machine Learning, Statistics and SAS Programming, Data Analysis and Data Mining, Probability, Stochastic Process, Queueing Theory, etc.
Categories Machine Learning
Publication Year 2016
ISBN 0387848576
Resource Verification ✓ Verified Direct PDF Available
Original Host Website FreeComputerBooks.com (freecomputerbooks.com)
File Format application/pdf (Portable Document Format)
Reported File Size 12991.8 KB (13,303,613 bytes)
Language ENGLISH
Catalog ID DOC-261572
Original Source Link Visit Source Page on freecomputerbooks.com »