Package: spnn 1.3.0

Romin Ebrahimi

spnn: Scale Invariant Probabilistic Neural Networks

Scale invariant version of the original PNN proposed by Specht (1990) <doi: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:Romin Ebrahimi [aut, cre]

spnn_1.3.0.tar.gz
spnn_1.3.0.zip(r-4.7-x86_64)spnn_1.3.0.zip(r-4.7-arm64)spnn_1.3.0.zip(r-4.6-x86_64)spnn_1.3.0.zip(r-4.6-arm64)
spnn_1.3.0.tar.gz(r-4.7-arm64)spnn_1.3.0.tar.gz(r-4.7-x86_64)spnn_1.3.0.tar.gz(r-4.6-arm64)spnn_1.3.0.tar.gz(r-4.6-x86_64)
spnn_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
spnn/json (API)

# Install 'spnn' in R:
install.packages('spnn', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

1.70 score 10 scripts 262 downloads 4 exports 3 dependencies

Last updated from:e41edccce4. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK124
linux-devel-x86_64OK94
source / vignettesOK169
linux-release-arm64OK96
linux-release-x86_64OK97
windows-devel-arm64OK196
windows-devel-x86_64OK94
windows-release-arm64OK213
windows-release-x86_64OK97
wasm-releaseOK85

Exports:cspnn.learncspnn.predictspnn.learnspnn.predict

Dependencies:MASSRcppRcppArmadillo