spnn: Scale Invariant Probabilistic Neural Networks

Scale invariant version of the original PNN proposed by Specht (1990) <doi:10.1016/0893-6080(90)90049-q> with the added functionality of allowing for smoothing along multiple dimensions while accounting for covariances within the data set. It is written in the R statistical programming language. Given a data set with categorical variables, we use this algorithm to estimate the probabilities of a new observation vector belonging to a specific category. This type of neural network provides the benefits of fast training time relative to backpropagation and statistical generalization with only a small set of known observations.

Package details

AuthorRomin Ebrahimi
MaintainerRomin Ebrahimi <romin.ebrahimi@utexas.edu>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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spnn documentation built on Jan. 9, 2020, 1:06 a.m.