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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "spnn" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'spnn: Scale Invariant Probabilistic Neural Networks'
version: 1.2.1
doi: 10.32614/CRAN.package.spnn
abstract: Scale invariant version of the original PNN proposed by Specht (1990) <https://doi.org/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.
authors:
- family-names: Ebrahimi
  given-names: Romin
  email: romin.ebrahimi@utexas.edu
repository: https://romin-ebrahimi.r-universe.dev
commit: 556140e58cce6aa99be929d1551ffe39afcd25d6
date-released: '2020-01-07'
contact:
- family-names: Ebrahimi
  given-names: Romin
  email: romin.ebrahimi@utexas.edu