README.md

In chasset/pnn: Probabilistic neural networks

PNN: Probabilistic neural network for the statistical language R

Description

The program PNN implements the algorithm proposed by Specht (1990). It is written in the R statistical langage. It solves a common problem in automatic learning. Knowing a set of observations described by a vector of quantitative variables, we classify them in a given number of groups. Then, the algorithm is trained with this dataset and should guess afterwards the group of any new observation. This neural network has the main advantage to begin generalization instantaneously even with a small set of known observations. It is delivered with four functions — learn, smooth, perf and guess — and a dataset. The functions are documented with examples and provided with unit tests.

License

This program is released under the GNU Affero General public license.

How to cite

Chasset P.-O. (2013). Probabilistic neural network for the R statistical language. Software.

Reference

Specht D.F. (1990). Probabilistic neural networks. Neural networks, 3(1):109–118.

R Core Team (2012). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org/.

chasset/pnn documentation built on March 24, 2022, 7 a.m.