Package: ssc 2.1-0

Christoph Bergmeir

ssc: Semi-Supervised Classification Methods

Provides a collection of self-labeled techniques for semi-supervised classification. In semi-supervised classification, both labeled and unlabeled data are used to train a classifier. This learning paradigm has obtained promising results, specifically in the presence of a reduced set of labeled examples. This package implements a collection of self-labeled techniques to construct a classification model. This family of techniques enlarges the original labeled set using the most confident predictions to classify unlabeled data. The techniques implemented can be applied to classification problems in several domains by the specification of a supervised base classifier. At low ratios of labeled data, it can be shown to perform better than classical supervised classifiers.

Authors:Mabel González [aut], Osmani Rosado-Falcón [aut], José Daniel Rodríguez [aut], Christoph Bergmeir [ths, cre], Isaac Triguero [ctb], José Manuel Benítez [ths]

ssc_2.1-0.tar.gz
ssc_2.1-0.zip(r-4.5)ssc_2.1-0.zip(r-4.4)ssc_2.1-0.zip(r-4.3)
ssc_2.1-0.tgz(r-4.4-any)ssc_2.1-0.tgz(r-4.3-any)
ssc_2.1-0.tar.gz(r-4.5-noble)ssc_2.1-0.tar.gz(r-4.4-noble)
ssc_2.1-0.tgz(r-4.4-emscripten)ssc_2.1-0.tgz(r-4.3-emscripten)
ssc.pdf |ssc.html
ssc/json (API)

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

Peer review:

Bug tracker:https://github.com/mabelc/ssc/issues

Datasets:
  • coffee - Time series data set
  • wine - Wine recognition data

On CRAN:

5.22 score 9 stars 1 packages 62 scripts 193 downloads 1 mentions 15 exports 1 dependencies

Last updated 5 years agofrom:4565f07e0f. Checks:ERROR: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesFAILNov 17 2024
R-4.5-winWARNINGNov 17 2024
R-4.5-linuxWARNINGNov 17 2024
R-4.4-winWARNINGNov 17 2024
R-4.4-macWARNINGNov 17 2024
R-4.3-winWARNINGNov 17 2024
R-4.3-macWARNINGNov 17 2024

Exports:coBCcoBCCombinecoBCGdemocraticdemocraticCombinedemocraticGoneNNselfTrainingselfTrainingGsetredsetredGsnnrcetriTrainingtriTrainingCombinetriTrainingG

Dependencies:proxy