This title covers a variety of predictive model combination methods, for both categorical and numeric target variables (bagging, boosting, etc.). It uses specific cases to illustrate particular points and makes reference to current literature (many references are from the early 2000s). Some MATLAB
Combining Pattern Classifiers: Methods and Algorithms
โ Scribed by Ludmila I. Kuncheva
- Publisher
- Wiley-Interscience
- Year
- 2004
- Tongue
- English
- Leaves
- 360
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Covering pattern classification methods, Combining Classifiers: Ideas and Methods focuses on the important and widely studied issue of how to combine several classifiers together in order to achieve improved recognition performance. It is one of the first books to provide unified, coherent, and expansive coverage of the topic and as such will be welcomed by those involved in the area. With case studies that bring the text alive and demonstrate 'real-world' applications it is destined to become essential reading.
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<p>A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition</p><p>The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of <
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining