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MLPUGS
View on CRAN: Click
here
Download and install MLPUGS package within the R console
Install from CRAN:
install.packages("MLPUGS")
Install from Github:
library("remotes")
install_github("cran/MLPUGS") Install by package version:
library("remotes")
install_version("MLPUGS", "0.2.0") Attach the package and use:
library("MLPUGS")
Maintained by
Mikhail Popov
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-07-06
Latest Update: 2016-07-06
Description:
An implementation of classifier chains (CC's) for multi-label
prediction. Users can employ an external package (e.g. 'randomForest',
'C50'), or supply their own. The package can train a single set of CC's or
train an ensemble of CC's -- in parallel if running in a multi-core
environment. New observations are classified using a Gibbs sampler since
each unobserved label is conditioned on the others. The package includes
methods for evaluating the predictions for accuracy and aggregating across
iterations and models to produce binary or probabilistic classifications.
How to cite:
Mikhail Popov (2016). MLPUGS: Multi-Label Prediction Using Gibbs Sampling (and Classifier Chains). R package version 0.2.0, https://cran.r-project.org/web/packages/MLPUGS. Accessed 11 Aug. 2026.
Previous versions and publish date:
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Other R packages that MLPUGS depends,
imports, suggests or enhances
Complete documentation for MLPUGS
Functions, R codes and Examples using
the MLPUGS R package
Some associated functions: MLPUGS-package . ecc . movies . predict.ECC . summary.PUGS . validate_pugs .
Some associated R codes: MLPUGS.R . data.R . ecc.R . pugs.R . Full MLPUGS package functions and examples
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