chasset/pnn: Probabilistic neural networks
Version 1.0.1

The program pnn implements the algorithm proposed by Specht (1990). It is written in the R statistical language. 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 datasets 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.

Getting started

Package details

AuthorPierre-Olivier Chasset
MaintainerPierre-Olivier Chasset <[email protected]>
LicenseAGPL
Version1.0.1
URL http://flow.chasset.net/pnn/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("chasset/pnn")
chasset/pnn documentation built on May 12, 2017, 2:22 a.m.