Description
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.
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Check History
OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
examples
Running examples in ‘ssc-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: coBC
> ### Title: CoBC method
> ### Aliases: coBC
>
> ### ** Examples
>
>
> library(ssc)
>
> ## Load W
...[truncated]...
caret::knn3,
+ learner.pars = list(k = 1),
+ pred = "predict")
Error in loadNamespace(x) : there is no package called ‘caret’
Calls: coBC ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart
Execution halted