Multiple Classifier Systems 9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010, Proceedings
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- Taschenbuch ausgewählt
- eBook
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Sprache:Englisch
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Verlag:Springer Berlin
- Springer 47,99 €
- Springer Berlin 49,99 € ausgewählt
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Auflage:2010
49,99 €
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
25.03.2010
Abbildungen
X, 77 illus., schwarz-weiss Illustrationen
Herausgeber
Neamat El Gayar + weitereVerlag
Springer BerlinSeitenzahl
328
Maße (L/B/H)
23,5/15,5/1,9 cm
Gewicht
522 g
Auflage
2010
Sprache
Englisch
ISBN
978-3-642-12126-5
Classifier Ensembles(I).- Weighted Bagging for Graph Based One-Class Classifiers.- Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers.- New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization.- Incremental Learning of New Classes in Unbalanced Datasets: Learn?+?+?.UDNC.- Tomographic Considerations in Ensemble Bias/Variance Decomposition.- Choosing Parameters for Random Subspace Ensembles for fMRI Classification.- Classifier Ensembles(II).- An Experimental Study on Ensembles of Functional Trees.- Multiple Classifier Systems under Attack.- SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning.- Unsupervised Change-Detection in Retinal Images by a Multiple-Classifier Approach.- A Double Pruning Algorithm for Classification Ensembles.- Estimation of the Number of Clusters Using Multiple Clustering Validity Indices.- Classifier Diversity.- "Good" and "Bad" Diversity in Majority Vote Ensembles.- Multi-information Ensemble Diversity.- Classifier Selection.- Dynamic Selection of Ensembles of Classifiers Using Contextual Information.- Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems.- Combining Multiple Kernels.- A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities.- Combining Multiple Kernels by Augmenting the Kernel Matrix.- Boosting and Bootstrapping.- Class-Separability Weighting and Bootstrapping in Error Correcting Output Code Ensembles.- Boosted Geometry-Based Ensembles.- Online Non-stationary Boosting.- Handwriting Recognition.- Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting.- Combining Committee-Based Semi-supervised and Active Learning and Its Application toHandwritten Digits Recognition.- Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition.- Applications.- Forecast Combination Strategies for Handling Structural Breaks for Time Series Forecasting.- A Multiple Classifier System for Classification of LIDAR Remote Sensing Data Using Multi-class SVM.- A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation.- A Multi-objective Sequential Ensemble for Cluster Structure Analysis and Visualization and Application to Gene Expression.- Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells.- An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction.- Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network.- Invited Papers.- Some Thoughts at the Interface of Ensemble Methods and Feature Selection.- Multiple Classifier Systems for the Recogonition of Human Emotions.- Erratum.- Erratum.
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