1. Fundamentals of pattern recognition -- 2. Base classifiers -- 3. Multiple classifier systems -- 4. Fusion of label outputs -- 5. Fusion of continuous-valued outputs -- 6. Classifier selection -- 7. Bagging and boosting -- 8. Miscellanea -- 9. Theoretical views and results -- 10. Diversity in classifier ensembles
Summary
"Replete with case studies and real-world applications, this text will be of interest to academics and researchers in the field seeking both new classification tools and new uses for the old ones."--BOOK JACKET
