| An Elementary Introduction to Statistical Learning Theory | | | Author:
| Kulkarni, Sanjeev
Harman, Gilbert | | Series title: | Wiley Series in Probability and Statistics Ser. | | ISBN: | 978-0-470-64183-5 | | Publication Date: | Aug 2011 | | Publisher: | John Wiley & Sons, Incorporated
| | Imprint: | Wiley | | Book Format: | Hardback | | List Price: | USD $130.95 | Book Description:
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- 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.
- 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.
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