{"product_id":"fabio-roli-multiple-classifier-systems-9783540438182","title":"Multiple Classifier Systems","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.","brand":"Springer","offers":[{"title":"Default Title","offer_id":53684010484054,"sku":null,"price":0.0,"currency_code":"EUR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0925\/5829\/5382\/files\/product_image_9783540438182_1.jpg?v=1778852347","url":"https:\/\/www.momoxbooks.com\/products\/fabio-roli-multiple-classifier-systems-9783540438182","provider":"momoxbooks","version":"1.0","type":"link"}