| 000 -LEADER |
|---|
| fixed length control field |
01680 a2200289 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240613150830.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240613b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| ISBN |
9780387848570 |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 HAS/E |
| 100 ## - MAIN ENTRY--AUTHOR NAME |
|---|
| Personal name |
Hastie, Trevor |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
The elements of statistical learning: data mining, inference, and prediction. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher |
Springer -- |
| Year of publication |
2009 |
| Place of publication |
United States of America -- |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Number of Pages |
xxii, 745p. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
* Overview of supervised learning<br/><br/>* Linear methods for regression<br/><br/>* Linear methods for classification<br/><br/>* Basis expansions and regularization<br/><br/>* Kernel smoothing methods<br/><br/>* Model assessment and selection<br/><br/>* Model inference and averaging<br/><br/>* Additive models, trees, and related methods<br/><br/>* Boosting and additive trees<br/><br/>* Neural networks<br/><br/>* Support vector machines and flexible discriminants<br/><br/>* Prototype methods and nearest-neighbors<br/><br/>* Unsupervised learning<br/><br/>* Random forests<br/><br/>* Ensemble learning<br/><br/>* Undirected graphical models<br/><br/>* High-dimensional problems |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
<br/>This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.<br/> |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Computer science |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Artificial Intelligence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Bioinformatics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Forecasting |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Computational intelligence |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Tibshirani, Robert |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Friedman, Jerome |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Book |
