Mode estimation with topographic maps
نویسندگان
چکیده
The paper reviews thoroughly a variety of issues related to mode estimation. The potential of self-organizing maps as an approach to mode detection is inquired here. The batch version of the standard SOM and a convex adjustment of it are compared with two kernel-based learning rules, namely, the generative topographic mapping and the kernelbased maximum entropy learning rule. A strategy for mode detection based on the previous topographic maps are tested on a number of synthetic gaussian data, as well as in a highly dimensional real-world example.
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