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The Elements of Statistical Learning Second Edition 2nd Data Mining, Inference
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eBay item number:335394118519
Item specifics
- Condition
- Subject
- Statistics
- ISBN
- 9780387848570
- Publication Name
- Elements of Statistical Learning : Data Mining, Inference, and Prediction
- Item Length
- 9.4in
- Publisher
- Springer New York
- Series
- Springer Series in Statistics Ser.
- Publication Year
- 2017
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 1.5in
- Item Width
- 6.5in
- Item Weight
- 51.2 Oz
- Number of Pages
- Xxii, 745 Pages
About this product
Product Information
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.
Product Identifiers
Publisher
Springer New York
ISBN-10
0387848576
ISBN-13
9780387848570
eBay Product ID (ePID)
69737567
Product Key Features
Publication Name
Elements of Statistical Learning : Data Mining, Inference, and Prediction
Format
Hardcover
Language
English
Series
Springer Series in Statistics Ser.
Publication Year
2017
Type
Textbook
Number of Pages
Xxii, 745 Pages
Dimensions
Item Length
9.4in
Item Height
1.5in
Item Width
6.5in
Item Weight
51.2 Oz
Additional Product Features
Number of Volumes
1 Vol.
Lc Classification Number
Q334-342
Edition Number
2
Reviews
From the reviews: "Like the first edition, the current one is a welcome edition to researchers and academicians equally.... Almost all of the chapters are revised.... The Material is nicely reorganized and repackaged, with the general layout being the same as that of the first edition.... If you bought the first edition, I suggest that you buy the second editon for maximum effect, and if you haven't, then I still strongly recommend you have this book at your desk. Is it a good investment, statistically speaking!" (Book Review Editor, Technometrics , August 2009, VOL. 51, NO. 3) From the reviews of the second edition: "This second edition pays tribute to the many developments in recent years in this field, and new material was added to several existing chapters as well as four new chapters ... were included. ... These additions make this book worthwhile to obtain ... . In general this is a well written book which gives a good overview on statistical learning and can be recommended to everyone interested in this field. The book is so comprehensive that it offers material for several courses." (Klaus Nordhausen, International Statistical Review, Vol. 77 (3), 2009) "The second edition ... features about 200 pages of substantial new additions in the form of four new chapters, as well as various complements to existing chapters. ... the book may also be of interest to a theoretically inclined reader looking for an entry point to the area and wanting to get an initial understanding of which mathematical issues are relevant in relation to practice. ... this is a welcome update to an already fine book, which will surely reinforce its status as a reference." (Gilles Blanchard, Mathematical Reviews, Issue 2012 d) "The book would be ideal for statistics graduate students ... . This book really is the standard in the field, referenced in most papers and books on the subject, and it is easy to see why. The book is very well written, with informative graphics on almost every other page. It looks great and inviting. You can flip the book open to any page, read a sentence or two and be hooked for the next hour or so." (Peter Rabinovitch, The Mathematical Association of America, May, 2012), From the reviews:"Like the first edition, the current one is a welcome edition to researchers and academicians equally…. Almost all of the chapters are revised.… The Material is nicely reorganized and repackaged, with the general layout being the same as that of the first edition.… If you bought the first edition, I suggest that you buy the second editon for maximum effect, and if you haven't, then I still strongly recommend you have this book at your desk. Is it a good investment, statistically speaking!" (Book Review Editor, Technometrics, August 2009, VOL. 51, NO. 3)From the reviews of the second edition:"This second edition pays tribute to the many developments in recent years in this field, and new material was added to several existing chapters as well as four new chapters … were included. … These additions make this book worthwhile to obtain … . In general this is a well written book which gives a good overview on statistical learning and can be recommended to everyone interested in this field. The book is so comprehensive that it offers material for several courses." (Klaus Nordhausen, International Statistical Review, Vol. 77 (3), 2009), From the reviews: "Like the first edition, the current one is a welcome edition to researchers and academicians equally…. Almost all of the chapters are revised.… The Material is nicely reorganized and repackaged, with the general layout being the same as that of the first edition.… If you bought the first edition, I suggest that you buy the second editon for maximum effect, and if you haven't, then I still strongly recommend you have this book at your desk. Is it a good investment, statistically speaking!" (Book Review Editor, Technometrics , August 2009, VOL. 51, NO. 3) From the reviews of the second edition: "This second edition pays tribute to the many developments in recent years in this field, and new material was added to several existing chapters as well as four new chapters … were included. … These additions make this book worthwhile to obtain … . In general this is a well written book which gives a good overview on statistical learning and can be recommended to everyone interested in this field. The book is so comprehensive that it offers material for several courses." (Klaus Nordhausen, International Statistical Review, Vol. 77 (3), 2009) The second edition … features about 200 pages of substantial new additions in the form of four new chapters, as well as various complements to existing chapters. … the book may also be of interest to a theoretically inclined reader looking for an entry point to the area and wanting to get an initial understanding of which mathematical issues are relevant in relation to practice. … this is a welcome update to an already fine book, which will surely reinforce its status as a reference. (Gilles Blanchard, Mathematical Reviews, Issue 2012 d) The book would be ideal for statistics graduate students … . This book really is the standard in the field, referenced in most papers and books on the subject, and it is easy to see why. The book is very well written, with informative graphics on almost every other page. It looks great and inviting. You can flip the book open to any page, read a sentence or two and be hooked for the next hour or so. (Peter Rabinovitch, The Mathematical Association of America, May, 2012)
Table of Content
Overview of Supervised Learning.- Linear Methods for Regression.- Linear Methods for Classification.- Basis Expansions and Regularization.- Kernel Smoothing Methods.- Model Assessment and Selection.- Model Inference and Averaging.- Additive Models, Trees, and Related Methods.- Boosting and Additive Trees.- Neural Networks.- Support Vector Machines and Flexible Discriminants.- Prototype Methods and Nearest-Neighbors.- Unsupervised Learning.- Random Forests.- Ensemble Learning.- Undirected Graphical Models.- High-Dimensional Problems: p ? N.
Copyright Date
2009
Topic
Probability & Statistics / General, Intelligence (Ai) & Semantics, Databases / Data Mining
Lccn
2008-941148
Dewey Decimal
006.31
Intended Audience
Scholarly & Professional
Dewey Edition
22
Illustrated
Yes
Genre
Computers, Mathematics
Item description from the seller
Seller assumes all responsibility for this listing.
eBay item number:335394118519
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| Shipping and handling | To | Service | Delivery*See Delivery notes |
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| US $6.99 | United States | Economy Shipping (USPS Media MailTM) | Estimated between Fri, Jun 7 and Mon, Jun 10 to 43230 |
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| Will usually ship within 3 business days of receiving cleared payment. |
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Absolutely stunning volume of books. Thank you so much! Very well packaged. Shipped and arrived quickly. The books are as described and pictured. Just lovely. Highly recommend this seller and would purchase from again! 🌟🌟🌟
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Item exactly as described. Item was well packed and protected in bubble wrap, newspaper and a sturdy oversized box. Shipped first business day after placing order and arrived early. Pretty much flawless all around. Thank you for the care you put into shipping this to me.
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