Applications of Supervised and Unsupervised Ensemble Methods
This book contains the extended papers presented at the 2nd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) held on 21-22 July, 2008 in Patras, Greece, in conjunction with the 18th European Conference on Artificial Intelligence (ECAI 2008). This workshop was a...
Enregistré dans:
| Auteur principal: | |
|---|---|
| Autres auteurs: | |
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2009. |
| Collection: | Studies in Computational Intelligence
245 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Applications of Supervised and Unsupervised Ensemble Methods, Texte imprimé, 9783642040344 • Applications of Supervised and Unsupervised Ensemble Methods, Texte imprimé, 9783642039980 • Applications of Supervised and Unsupervised Ensemble Methods, Texte imprimé, 9783642260773 • Applications of Supervised and Unsupervised Ensemble Methods, Texte imprimé, 9783642040344 • Applications of Supervised and Unsupervised Ensemble Methods, Texte imprimé, 9783642039980 • Applications of Supervised and Unsupervised Ensemble Methods, Texte imprimé, 9783642260773 |
Table des matières:
- An Ensemble Pruning Primer Evade Hard Multiple Classifier Systems A Personal Antispam System Based on a Behaviour-Knowledge Space Approach Weighted Decoding ECOC for Facial Action Unit Classification Prediction of Gene Function Using Ensembles of SVMs and Heterogeneous Data Sources Partitioner Trees for Classification: A New Ensemble Method Disturbing Neighbors Diversity for Decision Forests Improving Supervised Learning with Multiple Clusterings The Neighbors Voting Algorithm and Its Applications Clustering Ensembles with Active Constraints Verifiable Ensembles of Low-Dimensional Submodels for Multi-class Problems with Imbalanced Misclassification Costs Independent Data Model Selection for Ensemble Dispersion Forecasting Integrating Liknon Feature Selection and Committee Training Evaluating Hybrid Ensembles for Intelligent Decision Support for Intensive Care.