Fuzzy ARTMAP with relevance factor

Author(s): Andonie R. | Beiu V. | Sasu L. |

Year: 2003

Citation: Proceedings of the International Joint Conference on Neural Networks. IEEE, vol.3, 1975-1980.

Abstract: 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 the respective pair during the learning phase. Experimental results have shown that FAMR favorably compares with FAM and Probabilistic FAM (PFAM, defined in 111, 121) both as a classifier and as a probability estimator.

Topics: Machine Learning, Models: Fuzzy ARTMAP,

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