This book constitutes the refereed proceedings of the First International Workshop on Multiple Classifier Systems, MCS 2000, held in Cagliari, Italy in June 2000.
The 33 revised full papers presented together with five invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on theoretical issues, multiple classifier fusion, bagging and boosting, design of multiple classifier systems, applications of multiple classifier systems, document analysis, and miscellaneous applications.
Author(s): Thomas G. Dietterich (auth.)
Series: Lecture Notes in Computer Science 1857
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2000
Language: English
Pages: 408
Tags: Pattern Recognition; Artificial Intelligence (incl. Robotics); Image Processing and Computer Vision; Algorithm Analysis and Problem Complexity; Computation by Abstract Devices
Ensemble Methods in Machine Learning....Pages 1-15
Experiments with Classifier Combining Rules....Pages 16-29
The “Test and Select” Approach to Ensemble Combination....Pages 30-44
A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR....Pages 45-51
Multiple Classifier Combination Methodologies for Different Output Levels....Pages 52-66
A Mathematically Rigorous Foundation for Supervised Learning....Pages 67-76
Classifier Combinations: Implementations and Theoretical Issues....Pages 77-86
Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification....Pages 87-96
Complexity of Classification Problems and Comparative Advantages of Combined Classifiers....Pages 97-106
Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems....Pages 107-116
Combining Fisher Linear Discriminants for Dissimilarity Representations....Pages 117-126
A Learning Method of Feature Selection for Rough Classification....Pages 127-136
Analysis of a Fusion Method for Combining Marginal Classifiers....Pages 137-146
A hybrid projection based and radial basis function architecture....Pages 147-156
Combining Multiple Classifiers in Probabilistic Neural Networks....Pages 157-166
Supervised Classifier Combination through Generalized Additive Multi-model....Pages 167-176
Dynamic Classifier Selection....Pages 177-189
Boosting in Linear Discriminant Analysis....Pages 190-199
Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination....Pages 200-209
Applying Boosting to Similarity Literals for Time Series Classification....Pages 210-219
Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS....Pages 220-229
A New Evaluation Method for Expert Combination in Multi-expert System Designing....Pages 230-239
Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems....Pages 240-249
Self-Organizing Decomposition of Functions....Pages 250-259
Classifier Instability and Partitioning....Pages 260-269
A Hierarchical Multiclassifier System for Hyperspectral Data Analysis....Pages 270-279
Consensus Based Classification of Multisource Remote Sensing Data....Pages 280-289
Combining Parametric and Nonparametric Classifiers for an Unsupervised Updating of Land-Cover Maps....Pages 290-299
A Multiple Self-Organizing Map Scheme for Remote Sensing Classification....Pages 300-309
Use of Lexicon Density in Evaluating Word Recognizers....Pages 310-319
A Multi-expert System for Dynamic Signature Verification....Pages 320-329
A Cascaded Multiple Expert System for Verification....Pages 330-339
Architecture for Classifier Combination Using Entropy Measures....Pages 340-350
Combining Fingerprint Classifiers....Pages 351-361
Statistical Sensor Calibration for Fusion of Different Classifiers in a Biometric Person Recognition Framework....Pages 362-371
A Modular Neuro-Fuzzy Network for Musical Instruments Classification....Pages 372-382
Classifier Combination for Grammar-Guided Sentence Recognition....Pages 383-392
Shape Matching and Extraction by an Array of Figure-and-Ground Classifiers....Pages 393-402
