Package: spnn 1.2.1

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

spnn_1.2.1.tar.gz
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spnn.pdf |spnn.html
spnn/json (API)
NEWS

# Install 'spnn' in R:
install.packages('spnn', repos = c('https://romin-ebrahimi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/romin-ebrahimi/spnn/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

2.70 score 10 scripts 153 downloads 4 exports 3 dependencies

Last updated 7 months agofrom:556140e58c. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-win-x86_64NOTEOct 26 2024
R-4.5-linux-x86_64NOTEOct 26 2024
R-4.4-win-x86_64NOTEOct 26 2024
R-4.4-mac-x86_64NOTEOct 26 2024
R-4.4-mac-aarch64NOTEOct 26 2024
R-4.3-win-x86_64NOTEOct 26 2024
R-4.3-mac-x86_64NOTEOct 26 2024
R-4.3-mac-aarch64NOTEOct 26 2024

Exports:cspnn.learncspnn.predictspnn.learnspnn.predict

Dependencies:MASSRcppRcppArmadillo