Fusion methods for unsupervised learning ensembles
The application of a committee of experts or ensemble learning to artificial neural networks that apply unsupervised learning techniques is widely considered to enhance the effectiveness of such networks greatly. This book examines the potential of the ensemble meta-algorithm by describing and testi...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Udgivelse: | 1st ed. 2011. |
| Serier: | Studies in Computational Intelligence
322 |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Fusion Methods for Unsupervised Learning Ensembles, Texte imprimé, 9783642162046 • Fusion Methods for Unsupervised Learning Ensembles, Texte imprimé, 9783642423284 • Fusion Methods for Unsupervised Learning Ensembles, Texte imprimé, 9783642162046 • Fusion Methods for Unsupervised Learning Ensembles, Texte imprimé, 9783642162060 |
Indholdsfortegnelse:
- 1 Introduction 2 Modelling Human Learning: Artificial Neural Networks 3 The Committee of Experts Approach: Ensemble Learning 4 Use of Ensembles for Outlier Overcoming 5 Ensembles of Topology Preserving Maps 6 A Novel Fusion Algorithm for Topology-Preserving Maps.-7 Conclusions