The Elements of Statistical Learning: Data Mining, Inference, and Prediction 2nd
Specifications
| Country Of Origin | India |
| ISBN | 9780387848570 |
| Subject Area | Mathematics, Computers |
| Publisher | Springer New York |
| Item Length | 9.4 in |
| Publication Year | 2009 |
| Type | Textbook |
| Format | Hardcover |
| Language | English |
| Item Height | 1.5 in |
| Item Weight | 51.2 Oz |
| Item Width | 6.5 in |
| Number Of Pages | Xxii, 745 Pages |
"The Elements of Statistical Learning" is a comprehensive textbook authored by Trevor Hastie, Jerome Friedman, Robert Tibshirani, and J. H. Friedman. Published by Springer New York in 2009 as part of the Springer Series in Statistics, this hardcover book covers a range of subjects including probability and statistics, data mining, inference, and prediction. With a total of 745 pages, it serves as a valuable resource for adult and further education students looking to deepen their understanding of statistical learning and its applications in various fields. The book offers a thorough exploration of key concepts in a clear and accessible style, making it a popular choice among those interested in the intersection of computers, mathematics, and intelligence.
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