Invited Papers

• 
  Joydeep Ghosh: Multiclassifier Systems: Back to the Future. 1-15
• 
  Ji Zhu, Trevor Hastie: Support Vector Machines, Kernel Logistic Regression and Boosting. 16-26
• 
  Sarunas Raudys: Multiple Classification Systems in the Context of Feature Extraction and Selection. 27-41

Bagging and Boosting

• 
  Terry Windeatt, Gholamreza Ardeshir: Boosted Tree Ensembles for Solving Multiclass Problems. 42-51
• 
  Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, Thomas E. Moore, W. Philip Kegelmeyer: Distributed Pasting of Small Votes. 52-61
• 
  Marina Skurichina, Ludmila Kuncheva, Robert P. W. Duin: Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy. 62-71
• 
  Bruno Caprile, Cesare Furlanello, Stefano Merler: Highlighting Hard Patterns via AdaBoost Weights Evolution. 72-80
• 
  Ludmila I. Kuncheva, Christopher J. Whitaker: Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse. 81-90

Ensemble Learning and Neural Networks

• 
  Shuang Yang, Antony Browne, Phil D. Picton: Multistage Neural Network Ensembles. 91-97
• 
  Shimon Cohen, Nathan Intrator: Forward and Backward Selection in Regression Hybrid Network. 98-107
• 
  Amanda J. C. Sharkey: Types of Multinet System. 108-117
• 
  Francesco Mola, Roberta Siciliano: Discriminant Analysis and Factorial Multiple Splits in Recursive Partitioning for Data Mining. 118-126

Design Methodologies

• 
  Dymitr Ruta, Bogdan Gabrys: New Measure of Classifier Dependency in Multiple Classifier Systems. 127-136
• 
  Elzbieta Pekalska, Robert P. W. Duin, Marina Skurichina: A Discussion on the Classifier Projection Space for Classifier Combining. 137-148
• 
  David Windridge, Josef Kittler: On the General Application of the Tomographic Classifier Fusion Methodology. 149-158
• 
  Hakan Altinçay, Mübeccel Demirekler: Post-processing of Classifier Outputs in Multiple Classifier Systems. 159-168

Combination Strategies

• 
  Konstantinos Sirlantzis, Sanaul Hoque, Michael C. Fairhurst: Trainable Multiple Classifier Schemes for Handwritten Character Recognition. 169-178
• 
  Simon Günter, Horst Bunke: Generating Classifier Ensembles from Multiple Prototypes and Its Application to Handwriting Recognition. 179-188
• 
  Joseph T. Morgan, Alex Henneguelle, Melba M. Crawford, Joydeep Ghosh, Amy Neuenschwander: Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data. 189-200
• 
  Saso Dzeroski, Bernard Zenko: Stacking with Multi-response Model Trees. 201-211
• 
  Carmen Lai, David M. J. Tax, Robert P. W. Duin, Elzbieta Pekalska, Pavel Paclík: On Combining One-Class Classifiers for Image Database Retrieval. 212-221

Analysis and Performance Evaluation

• 
  Giorgio Valentini, Thomas G. Dietterich: Bias-Variance Analysis and Ensembles of SVM. 222-231
• 
  Fabio Roli, Sarunas Raudys, Gian Luca Marcialis: An Experimental Comparison of Fixed and Trained Fusion Rules for Crisp Classifier Outputs. 232-241
• 
  Arunas Janeliunas, Sarunas Raudys: Reduction of the Boasting Bias of Linear Experts. 242-251
• 
  Fabio Roli, Giorgio Fumera: Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers. 252-261

Applications

• 
  Francesco Masulli, Matteo Pardo, Giorgio Sberveglieri, Giorgio Valentini: Boosting and Classification of Electronic Nose Data. 262-271
• 
  Raimondo Schettini, Carla Brambilla, Claudio Cusano: Content-Based Classification of Digital Photos. 272-281
• 
  Julià Minguillón, Anne Rosemary Tate, Carles Arús, John R. Griffiths: Classifier Combination for In Vivo Magnetic Resonance Spectra of Brain Tumours. 282-292
• 
  Emilio Benfenati, Paolo Mazzatorta, Daniel Neagu, Giuseppina C. Gini: Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach. 293-303
• 
  Luigi P. Cordella, Massimo De Santo, Gennaro Percannella, Carlo Sansone, Mario Vento: A Multi-expert System for Movie Segmentation. 304-313
• 
  Josef Kittler, Marco Ballette, Jacek Czyz, Fabio Roli, Luc Vandendorpe: Decision Level Fusion of Intramodal Personal Identity Verification Experts. 314-324
• 
  Fabio Roli, Josef Kittler, Giorgio Fumera, Daniele Muntoni: An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems. 325-336

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