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spnn
View on CRAN: Click
here
Download and install spnn package within the R console
Install from CRAN:
install.packages("spnn")
Install from Github:
library("remotes")
install_github("cran/spnn")
Install by package version:
library("remotes")
install_version("spnn", "1.2.1")
Attach the package and use:
library("spnn")
Maintained by
Romin Ebrahimi
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-16
Latest Update: 2020-01-08
Description:
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.
How to cite:
Romin Ebrahimi (2018). spnn: Scale Invariant Probabilistic Neural Networks. R package version 1.2.1, https://cran.r-project.org/web/packages/spnn. Accessed 19 Apr. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for spnn
Functions, R codes and Examples using
the spnn R package
Some associated functions: cspnn.learn . cspnn.predict . spnn-package . spnn.learn . spnn.predict .
Some associated R codes: RcppExports.R . cspnn.learn.R . cspnn.predict.R . spnn-internal.R . spnn.learn.R . spnn.predict.R . Full spnn package functions and examples
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