By Ludmila I. Kuncheva
The paintings and technological know-how of mixing trend classifiers has flourished right into a prolific self-discipline because the first variation of Combining trend Classifiers used to be released in 2004. Dr. Kuncheva has plucked from the wealthy panorama of modern classifier ensemble literature the themes, tools, and algorithms that may consultant the reader towards a deeper figuring out of the basics, layout, and functions of classifier ensemble methods.
Thoroughly up to date, with MATLAB® code and perform facts units all through, Combining trend Classifiers includes:
- Coverage of Bayes choice idea and experimental comparability of classifiers
- Essential ensemble tools corresponding to Bagging, Random woodland, AdaBoost, Random subspace, Rotation wooded area, Random oracle, and blunder Correcting Output Code, between others
- Chapters on classifier choice, variety, and ensemble characteristic selection
With enterprise grounding within the basics of development acceptance, and that includes greater than a hundred and forty illustrations, Combining development Classifiers, moment Edition is a precious reference for postgraduate scholars, researchers, and practitioners in computing and engineering.
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Additional resources for Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms by Ludmila I. Kuncheva