Trevor Hastie, Robert Tibshirani, Jerome Friedman

The Elements of Statistical Learning (eBook, PDF)

Data Mining, Inference, and Prediction

• Format: PDF

Produktbeschreibung

This book covers modern regression, classification and clustering technology, from useful classical statistical tools to neural models. The audience is statisticians, engineers, applied researchers, financial analysts, and forecasters.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 536
• Erscheinungstermin: 11. November 2013
• Englisch
• ISBN-13: 9780387216065
• Artikelnr.: 43999288

Autorenporträt

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.