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.
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