Scale invariant version of the original PNN proposed by Specht (1990) <doi:10.1016/08936080(90)90049q> 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 


Author  Romin Ebrahimi 
Maintainer  Romin Ebrahimi <romin.ebrahimi@utexas.edu> 
License  GPL (>= 2) 
Version  1.2.1 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.