Sciweavers

Share
DAGSTUHL
2007

Relevance Matrices in LVQ

8 years 4 months ago
Relevance Matrices in LVQ
Abstract. We propose a new matrix learning scheme to extend Generalized Relevance Learning Vector Quantization (GRLVQ). By introducing a full matrix of relevance factors in the distance measure, correlations between different features and their importance for the classification scheme can be taken into account. In comparison to the weighted euclidean metric used for GRLVQ, this metric is more powerful to represent the internal structure of the data appropriately while maintaining its excellent generalization ability as large margin optimizer. The algorithm is tested and compared to alternative LVQ schemes using an artificial dataset and the image segmentation data from the UCI repository.
Petra Schneider
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where DAGSTUHL
Authors Petra Schneider
Comments (0)
books