Multiple Classifier Systems

Table of Contents

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   Book Overview
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   Chapter 1 Ensemble Methods in Machine Learning
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   Chapter 2 Experiments with Classifier Combining Rules
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   Chapter 3 The “Test and Select” Approach to Ensemble Combination
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   Chapter 4 A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR
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   Chapter 5 Multiple Classifier Combination Methodologies for Different Output Levels
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   Chapter 6 A Mathematically Rigorous Foundation for Supervised Learning
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   Chapter 7 Classifier Combinations: Implementations and Theoretical Issues
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   Chapter 8 Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification
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    Chapter 9 Complexity of Classification Problems and Comparative Advantages of Combined Classifiers
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    Chapter 10 Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems
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    Chapter 11 Combining Fisher Linear Discriminants for Dissimilarity Representations
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    Chapter 12 A Learning Method of Feature Selection for Rough Classification
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    Chapter 13 Analysis of a Fusion Method for Combining Marginal Classifiers
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    Chapter 14 A hybrid projection based and radial basis function architecture
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    Chapter 15 Combining Multiple Classifiers in Probabilistic Neural Networks
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    Chapter 16 Supervised Classifier Combination through Generalized Additive Multi-model
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    Chapter 17 Dynamic Classifier Selection
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    Chapter 18 Boosting in Linear Discriminant Analysis
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    Chapter 19 Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination
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    Chapter 20 Applying Boosting to Similarity Literals for Time Series Classification
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    Chapter 21 Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS
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    Chapter 22 A New Evaluation Method for Expert Combination in Multi-expert System Designing
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    Chapter 23 Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems
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    Chapter 24 Self-Organizing Decomposition of Functions
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    Chapter 25 Classifier Instability and Partitioning
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    Chapter 26 A Hierarchical Multiclassifier System for Hyperspectral Data Analysis
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    Chapter 27 Consensus Based Classification of Multisource Remote Sensing Data
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    Chapter 28 Combining Parametric and Nonparametric Classifiers for an Unsupervised Updating of Land-Cover Maps
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    Chapter 29 A Multiple Self-Organizing Map Scheme for Remote Sensing Classification
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    Chapter 30 Use of Lexicon Density in Evaluating Word Recognizers
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    Chapter 31 A Multi-expert System for Dynamic Signature Verification
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    Chapter 32 A Cascaded Multiple Expert System for Verification
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    Chapter 33 Architecture for Classifier Combination Using Entropy Measures
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    Chapter 34 Combining Fingerprint Classifiers
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    Chapter 35 Statistical Sensor Calibration for Fusion of Different Classifiers in a Biometric Person Recognition Framework
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    Chapter 36 A Modular Neuro-Fuzzy Network for Musical Instruments Classification
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    Chapter 37 Classifier Combination for Grammar-Guided Sentence Recognition
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    Chapter 38 Shape Matching and Extraction by an Array of Figure-and-Ground Classifiers