pnn: Probabilistic neural networks

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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.

Author
Pierre-Olivier Chasset
Date of publication
2013-05-07 22:17:22
Maintainer
Pierre-Olivier Chasset <pierre-olivier@chasset.net>
License
AGPL
Version
1.0.1
URLs

View on CRAN

Man pages

guess
Guess
learn
Learn
norms
Norms
perf
Perf
pnn-package
PNN
smooth
Smooth

Files in this package

pnn
pnn/MD5
pnn/TODO.md
pnn/README.md
pnn/R
pnn/R/what-else.R
pnn/R/smooth.R
pnn/R/pnn-package.r
pnn/R/perf.r
pnn/R/learn.R
pnn/R/kernel.R
pnn/R/holdout.R
pnn/R/guess.r
pnn/R/guess-probabilities.R
pnn/R/guess-category.R
pnn/R/data-norms.R
pnn/R/create.R
pnn/NEWS
pnn/NAMESPACE
pnn/man
pnn/man/smooth.Rd
pnn/man/pnn-package.Rd
pnn/man/perf.Rd
pnn/man/norms.Rd
pnn/man/learn.Rd
pnn/man/guess.Rd
pnn/inst
pnn/inst/tests
pnn/inst/tests/test-smooth.R
pnn/inst/tests/test-perf.R
pnn/inst/tests/test-learn.R
pnn/inst/tests/test-kernel.R
pnn/inst/tests/test-holdout.R
pnn/inst/tests/test-guess.R
pnn/inst/tests/test-create.R
pnn/inst/CITATION
pnn/DESCRIPTION
pnn/data
pnn/data/norms.rda