A SOM based model combination strategy

Authors:
Cristofer Englund;Antanas Verikas
Affiliations:
Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden;Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Year:
2005

Citing 10
Cited 3

Fusion of handwritten word classifiers

Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Combination of Multiple Classifiers Using Local Accuracy Estimates

IEEE Transactions on Pattern Analysis and Machine Intelligence
Averaging regularized estimators

Neural Computation
On Combining Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Soft combination of neural classifiers: a comparative study

Pattern Recognition Letters
Self-Organizing Maps

Self-Organizing Maps
Fusing Neural Networks Through Space Partitioning and Fuzzy Integration

Neural Processing Letters
Implementing Relevance Feedback as Convolutions of Local Neighborhoods on Self-Organizing Maps

ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Self-Organizing Decomposition of Functions in the Context of a Unified Framework for Multiple Classifier Systems

MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Divide-and-conquer approach for brain machine interfaces: nonlinear mixture of competitive linear models

Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03

A SOM-based data mining strategy for adaptive modelling of an offset lithographic printing process

Engineering Applications of Artificial Intelligence
Ink flow control by multiple models in an offset lithographic printing process

Computers and Industrial Engineering
Combining traditional and neural-based techniques for ink feed control in a newspaper printing press

ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

A SOM based model combination strategy, allowing to create adaptive – data dependent – committees, is proposed. Both, models included into a committee and aggregation weights are specific for each input data point analyzed. The possibility to detect outliers is one more characteristic feature of the strategy.