Title :
Batch map extensions of the kernel-based maximum entropy learning rule
Author :
Gautama, Temujin ; Van Hulle, Marc M.
Author_Institution :
Lab. voor Neuro en Psychofysiologie, Katholieke Univ. Leuven, Belgium
fDate :
3/1/2006 12:00:00 AM
Abstract :
In this letter, two batch-map extensions are described for the kernel-based maximum entropy learning rule (kMER). In the first, the weights are iteratively set to weighted component-wise medians, while in the second the generalized median is used, enabling kMER to process symbolic data. Simulations are performed to illustrate the extensions.
Keywords :
iterative methods; learning (artificial intelligence); maximum entropy methods; self-organising feature maps; batch map extensions; iterative method; kernel-based maximum entropy learning rule; symbolic data processing; weighted component-wise medians; Cooling; Educational programs; Entropy; Iterative algorithms; Neurons; Psychology; Temperature control; Terminology; Training data; Vector quantization; Batch map; generalized median; kMER; Algorithms; Artificial Intelligence; Computer Simulation; Decision Support Techniques; Entropy; Image Interpretation, Computer-Assisted; Models, Theoretical; Neural Networks (Computer); Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2006.871722
