Multiple Classifier Systems (eBook)

9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010, Proceedings

Neamat El Gayar, Josef Kittler, Fabio Roli (Herausgeber)

eBook Download: PDF

2010 | 2010
X, 328 Seiten
Springer Berlin (Verlag)
9783642121272 (ISBN)

Inhalt

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 to Handwritten 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.

Produkt-Details

• Erscheint lt. Verlag: 26.3.2010
• Reihe/Serie: Lecture Notes in Computer Science
• Reihe/Serie: Theoretical Computer Science and General Issues
• Verlagsort: Berlin
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Web / Internet
• Schlagworte: algorithms • ants • Boosting • bootstrap aggregating • classification • Clustering • Hidden Markov Model • Markov model
• ISBN-13: 9783642121272 / 9783642121272