Package: spnn
Type: Package
Title: Scale Invariant Probabilistic Neural Networks
Version: 1.1
Date: 2018-03-15
Author: Romin Ebrahimi
Maintainer: Romin Ebrahimi <romin.ebrahimi@utexas.edu>
Description: 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.
License: GPL (>= 2)
Imports: MASS (>= 3.1-20)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-03-20 16:42:31 UTC; romin
Repository: CRAN
Date/Publication: 2018-03-20 18:21:50 UTC
