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Multiple Classifier Systems

Multiple Classifier Systems Computer Science

Multiple Classifier Systems

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Description
Invited Papers.- Multiclassifier Systems: Back to the Future.- Support Vector Machines, Kernel Logistic Regression and Boosting.- Multiple Classification Systems in the Context of Feature Extraction and Selection.- Bagging and Boosting.- Boosted Tree Ensembles for Solving Multiclass Problems.- Distributed Pasting of Small Votes.- Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy.- Highlighting Hard Patterns via AdaBoost Weights Evolution.- Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse.- Ensemble Learning and Neural Networks.- Multistage Neural Network Ensembles.- Forward and Backward Selection in Regression Hybrid Network.- Types of Multinet System.- Discriminant Analysis and Factorial Multiple Splits in Recursive Partitioning for Data Mining.- Design Methodologies.- New Measure of Classifier Dependency in Multiple Classifier Systems.- A Discussion on the Classifier Projection Space for Classifier Combining.- On the General Application of the Tomographic Classifier Fusion Methodology.- Post-processing of Classifier Outputs in Multiple Classifier Systems.- Combination Strategies.- Trainable Multiple Classifier Schemes for Handwritten Character Recognition.- Generating Classifier Ensembles from Multiple Prototypes and Its Application to Handwriting Recognition.- Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data.- Stacking with Multi-response Model Trees.- On Combining One-Class Classifiers for Image Database Retrieval.- Analysis and Performance Evaluation.- Bias-Variance Analysis and Ensembles of SVM.- An Experimental Comparison of Fixed and Trained Fusion Rules for Crisp Classifier Outputs.- Reduction of the Boasting Bias of Linear Experts.-Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers.- Applications.- Boosting and Classification of Electronic Nose Data.- Content-Based Classification of Digital Photos.- Classifier Combination for In Vivo Magnetic Resonance Spectra of Brain Tumours.- Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach.- A Multi-expert System for Movie Segmentation.- Decision Level Fusion of Intramodal Personal Identity Verification Experts.- An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems.
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
352
Release Date:
2008-06-13
Publication Date:
2002-06-12
Publisher:
Springer
Languages:
Original: English
ISBN10:
3540438181
ISBN13:
9783540438182
GPSR Manufacturer Reference:
Weight:
534 g
Height:
155 cm
Width:
235 cm
Thickness:
20 cm
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