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yap
View on CRAN: Click
here
Download and install yap package within the R console
Install from CRAN:
install.packages("yap")
Install from Github:
library("remotes")
install_github("cran/yap")
Install by package version:
library("remotes")
install_version("yap", "0.1.1")
Attach the package and use:
library("yap")
Maintained by
WenSui Liu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-15
Latest Update: 2023-04-07
Description:
Another implementation of probabilistic neural network in R
based on Specht (1990) . It is applicable to the
pattern recognition with a N-level response, where N > 2.
How to cite:
WenSui Liu (2020). yap: Yet Another Probabilistic Neural Network. R package version 0.1.1, https://cran.r-project.org/web/packages/yap
Other packages that cited yap R package
View yap citation profile
Other R packages that yap depends,
imports, suggests or enhances
Functions, R codes and Examples using
the yap R package
Some associated functions: dummies . folds . gen_latin . gen_sobol . gen_unifm . logl . pnn.fit . pnn.imp . pnn.optmiz_logl . pnn.parpred . pnn.pfi . pnn.predict . pnn.predone . pnn.search_logl . pnn.x_imp . pnn.x_pfi .
Some associated R codes: dummies.R . folds.R . gen_latin.R . gen_sobol.R . gen_unifm.R . logl.R . pnn.fit.R . pnn.imp.R . pnn.optmiz_logl.R . pnn.parpred.R . pnn.pfi.R . pnn.predict.R . pnn.predone.R . pnn.predonev1.R . pnn.search_logl.R . pnn.x_imp.R . pnn.x_pfi.R . Full yap package functions and examples
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