MARC details
| 000 -LEADER |
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| fixed length control field |
02708nam a22002417a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20210217143631.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
210217b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781461471370 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
519.5 |
| Item number |
GAR |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Gareth James, |
| 245 ## - TITLE STATEMENT |
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| Title |
An introduction to statistical learning : |
| Remainder of title |
with applications in R |
| Statement of responsibility, etc. |
James Gareth |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
New York : |
| Name of publisher, distributor, etc. |
Springer, |
| Date of publication, distribution, etc. |
©2013 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Page number |
xiv, 426 pages : |
| Other physical details |
illustrations (some color) ; |
| Dimensions |
24 cm. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Title |
Introduction --<br/> |
| -- |
Statistical learning --<br/> |
| -- |
Linear regression --<br/> |
| -- |
Classification --<br/> |
| -- |
Resampling methods --<br/> |
| -- |
Linear model selection and regularization --<br/> |
| -- |
Moving beyond linearity --<br/> |
| -- |
Tree-based methods --<br/> |
| -- |
Support vector machines --<br/> |
| -- |
Unsupervised learning. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. Provides tools for Statistical Learning that are essential for practitioners in science, industry and other fields. Analyses and methods are presented in R |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical statistics. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Mathematical models. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical statistics -- Problems, exercises, etc. |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Daniela Witten, |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Trevor Hastie, |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Robert Tibshirani. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
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2694 |
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2695 |
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2696 |
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2697 |
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2698 |
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2699 |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) |
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2700 |
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2701 |
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2702 |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) |
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2703 |
