The Elements of Statistical Learning. Data Mining, Inference, and Prediction (Statistics for Engineering and Information Science)

Trevor Hastie

ISBN 10: 0387952845 / ISBN 13: 9780387952840

Published by Springer, 2003

About this Item

Ausreichend/Acceptable: Exemplar mit vollständigem Text und sämtlichen Abbildungen oder Karten. Schmutztitel oder Vorsatz können fehlen. Einband bzw. Schutzumschlag weisen unter Umständen starke Gebrauchsspuren auf. / Describes a book or dust jacket that has the complete text pages (including those with maps or plates) but may lack endpapers, half-title, etc. (which must be noted). Binding, dust jacket (if any), etc may also be worn.

Seller Inventory # M00387952845-B

Bibliographic Details

• Title: The Elements of Statistical Learning. Data Mining, Inference, and Prediction (Statistics for Engineering and Information Science)
• Publisher: Springer
• Publication Date: 2003
• Language: English
• ISBN 10: 0387952845
• ISBN 13: 9780387952840
• Binding: Hardcover
• Condition: acceptable

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.