A Fuzzy ARTMAP Probability Estimator with Relevance Factor
نویسندگان
چکیده
An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzzy ARTMAP with Relevance factor (FAMR), uses a relevance factor assigned to each sample pair, proportional to the importance of that pair during the learning phase. We prove that our probability estimator is correct. The FAMR can be used both as a classifier and as a probability estimator.
منابع مشابه
Convergence properties of a fuzzy ARTMAP network
FAMR (Fuzzy ARTMAP with Relevance factor) is a FAM (Fuzzy ARTMAP) neural network used for classification, probability estimation [3], [2], and function approximation [4]. FAMR uses a relevance factor assigned to each sample pair, proportional to the importance of that pair during the learning phase. Due to its incremental learning capability, FAMR can efficiently process large data sets and is ...
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