Multiple classifier systems

Multiple Classifier Systems: Second International Workshop, MCS 2001 Cambridge, UK, July 2–4, 2001 Proceedings
Author: Josef Kittler, Fabio Roli
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-42284-6
DOI: 10.1007/3-540-48219-9

Table 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