Introduction Statistical Learning: First Edition (8 results)
Language: English
Published by SPRINGER 2013
Series: Springer Texts in Statistics, Book 71 of 111. Book 71 of 111 - Springer Texts in Statistics
- Hardcover
- First Edition
Seller: Textbooks_Source, Columbia, MO, U.S.A.Textbooks_Source
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hardcover. Condition: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Language: English
Published by Springer 2013
Series: Springer Texts in Statistics, Book 71 of 111. Book 71 of 111 - Springer Texts in Statistics
- Hardcover
- First Edition
Seller: Pulpfiction Books, Vancouver, BC, CanadaPulpfiction Books
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Hardcover. Condition: Near Fine. 1st Edition. First edition, later printing. As new hardback issued without dust jacket, clean and unmarked.
Language: English
Published by SPRINGER 2013
Series: Springer Texts in Statistics, Book 71 of 111. Book 71 of 111 - Springer Texts in Statistics
- Hardcover
- First Edition
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Hardcover. Condition: As New. 1st Edition. Like new, excellent condition, clean inside and out, no highlighting marks or written notes on any of the pages.
Language: English
Published by Springer 2023
Series: Springer Texts in Statistics, Book 104 of 111. Book 104 of 111 - Springer Texts in Statistics
- Hardcover
- First Edition
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Hardcover. Condition: Fine. 1st Edition. gated Perfect condition gift quality, shrink-wrapped and shipped in bubble mailer.
Language: English
Published by Springer 2013
Series: Springer Texts in Statistics, Book 71 of 111. Book 71 of 111 - Springer Texts in Statistics
- Hardcover
- First Edition
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Hardcover. Condition: New. 1st Edition. Springer (2013). New Hardcover. 9.5"x6.3"x1.0". be47.
Language: English
Published by Springer 2023
Series: Springer Texts in Statistics, Book 104 of 111. Book 104 of 111 - Springer Texts in Statistics
- Hardcover
- First Edition
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Hardcover. Condition: Good. 1st Edition. We only honor returns for quality issues and won't accept reasons such as 'change my mind', 'find a better price', or 'school book requirement change', etc.
- Hardcover
- First Edition
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Condition: New. * Serves as a fundamental introduction to statistical learning theory and its role in understanding human learning and inductive reasoning. * Topics of coverage include: probability, pattern recognition, optimal Bayes decision rule, nearest neighbor rule, kernel rules, neural networks, and support vector machines…. Series: Wiley Series in Probability and Statistics. Num Pages: 232 pages, Illustrations. BIC Classification: PBT; UYQM. Category: (P) Professional & Vocational. Dimension: 237 x 162 x 17. Weight in Grams: 496. . 2011. 1st Edition. Hardcover. . . . .
- Hardcover
- First Edition
- Print on Demand
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Hardcover. Condition: new. Hardcover. A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a compre…hensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these areas at a level and in a way that is not often found in other books on the topic, the authors present the basic theory behind contemporary machine learning and uniquely utilize its foundations as a framework for philosophical thinking about inductive inference. Promoting the fundamental goal of statistical learning, knowing what is achievable and what is not, this book demonstrates the value of a systematic methodology when used along with the needed techniques for evaluating the performance of a learning system. First, an introduction to machine learning is presented that includes brief discussions of applications such as image recognition, speech recognition, medical diagnostics, and statistical arbitrage. To enhance accessibility, two chapters on relevant aspects of probability theory are provided. Subsequent chapters feature coverage of topics such as the pattern recognition problem, optimal Bayes decision rule, the nearest neighbor rule, kernel rules, neural networks, support vector machines, and boosting. Appendices throughout the book explore the relationship between the discussed material and related topics from mathematics, philosophy, psychology, and statistics, drawing insightful connections between problems in these areas and statistical learning theory. All chapters conclude with a summary section, a set of practice questions, and a reference sections that supplies historical notes and additional resources for further study. An Elementary Introduction to Statistical Learning Theory is an excellent book for courses on statistical learning theory, pattern recognition, and machine learning at the upper-undergraduate and graduate levels. It also serves as an introductory reference for researchers and practitioners in the fields of engineering, computer science, philosophy, and cognitive science that would like to further their knowledge of the topic. * Serves as a fundamental introduction to statistical learning theory and its role in understanding human learning and inductive reasoning. * Topics of coverage include: probability, pattern recognition, optimal Bayes decision rule, nearest neighbor rule, kernel rules, neural networks, and support vector machines. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
