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This study proposed supervised learning probabilistic neural networks (SLPNN) which have three kinds of network parameters: variable weights representing the importance of input variables, the reciprocal of kernel radius representing the effective range of data, and data weights representing the data reliability. These three kinds of parameters can be adjusted through training. We tested three artificial...
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