TY  - BOOK
AU  - Gayar,Neamat
AU  - Kittler,Josef
AU  - Roli,Fabio
ED  - SpringerLink (Online service)
TI  - Multiple Classifier Systems: 9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010. Proceedings 
T2  - Lecture Notes in Computer Science,
SN  - 9783642121272
AV  - QA76.76.A65 
U1  - 005.7 23
PY  - 2010///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Computer software
KW  - Database management
KW  - Data mining
KW  - Information systems
KW  - Optical pattern recognition
KW  - Computer Science
KW  - Information Systems Applications (incl.Internet)
KW  - Pattern Recognition
KW  - Algorithm Analysis and Problem Complexity
KW  - Computation by Abstract Devices
KW  - Database Management
KW  - Data Mining and Knowledge Discovery
N1  - 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
UR  - http://dx.doi.org/10.1007/978-3-642-12127-2
ER  -