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.
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. Continue reading →
This program is released under the GNU Affero General public license.
Chasset P.-O. (2013). Probabilistic neural network for the R statistical language. Software, http://flow.chasset.net/pnn/.
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/.
Complete documentations with examples.
Suppress 'skin' dataset.
Clean the user interface with only four exported functions