Batch Map Extensions of the Kernel-Based Maximum Entropy Learning Rule
Temujin Gautama, M.M. VanHulle · IEEE Transactions on Neural Networks · 2006
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.