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, New York

About this Item

Hardcover edition in Poor condition. 5th printing. The bottom center of the covers are show heavy wear exposing the boards. Corners are bumped. Spine ends crushed. The binding is in good shape but the book is slightly rolled backwards. Small abrasion to the front flyleaf. The interior pages are heavily creased at the front edge. Feel free to contact me for pictures. The book will be carefully packaged for shipment for protection from the elements. USPS electronic tracking number issued free of charge.

Seller Inventory # 15217

Bibliographic Details

• Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)
• Publisher: Springer, New York
• Language: English
• ISBN 10: 0387952845
• ISBN 13: 9780387952840
• Binding: Hardcover
• Edition: First Edition.
• Condition: Poor
• Dust Jacket Condition: No Jacket

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.