Multiple Classifier Systems First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2000, 2000
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| Edition: | 1st ed. 2000 |
| Series: | Lecture Notes in Computer Science
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- A hybrid projection based and radial basis function architecture
- Combining Multiple Classifiers in Probabilistic Neural Networks
- Supervised Classifier Combination through Generalized Additive Multi-model
- Dynamic Classifier Selection
- Boosting in Linear Discriminant Analysis
- Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination
- Applying Boosting to Similarity Literals for Time Series Classification
- Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS
- A New Evaluation Method for Expert Combination in Multi-expert System Designing
- Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems
- Self-Organizing Decomposition of Functions
- Classifier Instability and Partitioning
- A Hierarchical Multiclassifier System for Hyperspectral Data Analysis.-Consensus Based Classification of Multisource Remote Sensing Data
- Combining Parametric and Nonparametric Classifiers for an Unsupervised Updating of Land-Cover Maps
- A Multiple Self-Organizing Map Scheme for Remote Sensing Classification
- Use of Lexicon Density in Evaluating Word Recognizers
- A Multi-expert System for Dynamic Signature Verification
- A Cascaded Multiple Expert System for Verification
- Architecture for Classifier Combination Using Entropy Measures
- Combining Fingerprint Classifiers
- Statistical Sensor Calibration for Fusion of Different Classifiers in a Biometric Person Recognition Framework
- A Modular Neuro-Fuzzy Network for Musical Instruments Classification
- Classifier Combination for Grammar-Guided Sentence Recognition
- Shape Matching and Extraction by an Array of Figure-and-Ground Classifiers
- Ensemble Methods in Machine Learning
- Experiments with Classifier Combining Rules
- The “Test and Select” Approach to Ensemble Combination
- A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR
- Multiple Classifier Combination Methodologies for Different Output Levels
- A Mathematically Rigorous Foundation for Supervised Learning
- Classifier Combinations: Implementations and Theoretical Issues
- Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification
- Complexity of Classification Problems and Comparative Advantages of Combined Classifiers
- Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems
- Combining Fisher Linear Discriminants for Dissimilarity Representations
- A Learning Method of Feature Selection for Rough Classification
- Analysis of a Fusion Method for Combining Marginal Classifiers