The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)

Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome

ISBN 10: 0387952845 / ISBN 13: 9780387952840

Published by Springer, 2003

About this Item

There is handwriting, stickers or numbers inside the front cover Cover/Case has some rubbing and edgewear. Access codes, CDs, slipcovers and other accessories may not be included.

Seller Inventory # 2Y6RVK006B1Q_ns

Bibliographic Details

• Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)
• Publisher: Springer
• Publication Date: 2003
• Language: English
• ISBN 10: 0387952845
• ISBN 13: 9780387952840
• Binding: Hardcover
• Condition: Good

About this title

Synopsis

2003 edition

About the Author

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.