Multiple Classifier Systems

Multiple Classifier Systems: Second International Workshop, MCS 2001 Cambridge, UK, July 2–4, 2001 ProceedingsAuthor: Josef Kittler, Fabio Roli Published by Springer Berlin Heidelberg ISBN: 978-3-540-42284-6 DOI: 10.1007/3-540-48219-9Table of Contents:Bagging and the Random Subspace Method for Redundant Feature Spaces
Performance Degradation in Boosting
A Generalized Class of Boosting Algorithms Based on Recursive Decoding Models
Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis
Learning Classification RBF Networks by Boosting
Data Complexity Analysis for Classifier Combination
Genetic Programming for Improved Receiver Operating Characteristics
Methods for Designing Multiple Classifier Systems
Decision-Level Fusion in Fingerprint Verification
Genetic Algorithms for Multi-classifier System Configuration: A Case Study in Character Recognition
Combined Classification of Handwritten Digits Using the ‘Virtual Test Sample Method’
Averaging Weak Classifiers
Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds
Multiple Classifier Systems Based on Interpretable Linear Classifiers
Least Squares and Estimation Measures via Error Correcting Output Code
Dependence among Codeword Bits Errors in ECOC Learning Machines: An Experimental Analysis
Information Analysis of Multiple Classifier Fusion?
Limiting the Number of Trees in Random Forests
Learning-Data Selection Mechanism through Neural Networks Ensemble
A Multi-SVM Classification System