Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Linear Programming Boosting via Column Generation
Machine Learning
Data visualisation and manifold mapping using the ViSOM
Neural Networks - New developments in self-organizing maps
Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit
Data Mining and Knowledge Discovery
Neural Computation
Outlier resistant PCA ensembles
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Maximum likelihood topology preserving ensembles
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
ViSOM - a novel method for multivariate data projection and structure visualization
IEEE Transactions on Neural Networks
A nonlinear projection method based on Kohonen's topology preserving maps
IEEE Transactions on Neural Networks
A WeVoS-CBR Approach to Oil Spill Problem
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Application of Topology Preserving Ensembles for Sensory Assessment in the Food Industry
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Automated Ham Quality Classification Using Ensemble Unsupervised Mapping Models
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Ensemble Methods for Boosting Visualization Models
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
MACSDE: Multi-Agent Contingency Response System for Dynamic Environments
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
A forecasting solution to the oil spill problem based on a hybrid intelligent system
Information Sciences: an International Journal
A weighted voting summarization of SOM ensembles
Data Mining and Knowledge Discovery
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Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping models with some basic classifier ensemble and boosting techniques in order to increase the stability conditions and, as an extension, the classification capabilities of the former. A study and comparison of the performance of some novel and classical ensemble techniques are presented in this paper to test their suitability, both in the fields of data visualization and classification when combined with topology preserving models such as the SOM, ViSOM or ML-SIM.