Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Language: English
Published by Apress, 2018
- Softcover
- New

Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
AbeBooks seller since January 6, 2003
Condition: New
US$ 145.05
Quantity: 2 available
Add to basketItem description from seller
537 pages. 10.00x7.01x1.06 inches. In Stock.
Seller Inventory # x-1484233352
- Title
- Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
- Author
- Masters, Timothy
- Publisher
- Apress
- Publication year
- 2018
- Condition
- Brand New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1484233352
- ISBN 13
- 9781484233351
- Item weight
- 0.93 kilograms
- Compute entropy to detect problematic predictors
- Improve numeric predictions using constrained and unconstrained combinations, variance-weighted interpolation, and kernel-regression smoothing
- Carry out classification decisions using Borda counts, MinMax and MaxMin rules, union and intersection rules, logistic regression, selection by local accuracy, maximization of the fuzzy integral, and pairwise coupling
- Harness information-theoretic techniques to rapidly screen large numbers of candidate predictors, identifying those that are especially promising
- Use Monte-Carlo permutation methods to assessthe role of good luck in performance results
- Compute confidence and tolerance intervals for predictions, as well as confidence levels for classification decisions
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About the Author
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Revaluation Books
Exeter, United Kingdom
AbeBooks seller since January 6, 2003
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Edward Bowditch Ltd
Exstowe, Exton
Exeter, United Kingdom EX3 0PP
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