The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
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Select a product to estimate shipping.“The Elements of Statistical Learning” is a comprehensive textbook offering a rigorous introduction to the field of statistical learning. This second edition builds upon the original’s foundational concepts, providing a detailed exploration of data mining, inference, and prediction techniques.
Key Highlights
- Gain a solid understanding of core statistical learning methods.
- Explore a wide range of algorithms for data analysis and modeling.
- Benefit from clear explanations and numerous examples illustrating practical applications.
- Suitable for readers with a background in mathematics and statistics.
Useful Facts
- Publisher: Springer
- Publication Date: February 9, 2009
- Edition: Second Edition 2009
- Language: English
- Pages: 767
- Dimensions: 9.3 x 6 x 1.4 inches
Good Fit For
- Students and researchers in computer science, statistics, and related fields.
- Data scientists and analysts seeking to deepen their knowledge of statistical modeling.
- Anyone interested in learning the theoretical foundations of machine learning.
| Main Specification | |
|---|---|
| 주요 특징 | by Trevor Hastie (Author) or Robert Tibshirani (Author) or Jerome Friedman (Author) & 0 more Format: Hardcover |
| 출판일 | 2009 or February 9 |
| 제품 무게 | 3.1 파운드 |
| Product information | |
| * 이름 | 한국어 |
| Others | |
| 제품 유형 | Intelligence & Semantics |
| 계정 만들기 | Second Edition 2009 |
| 주요연혁 | Springer |
| 인쇄 길이 | 767 pages |
| 사이트맵 | 0387848576 |
| 사이트맵 | 978-0387848570 |
| 크기 (mm) | 9.3 x 6 x 1.4 inches |
| 사이트맵 | 0387848576 |
| 사이트맵 | 978-0387848570 |