RSSL: R Semi-Supervised Learning Package

In RSSL: Implementations of Semi-Supervised Learning Approaches for Classification

R Semi-Supervised Learning Package

Description

RSSL provides implementations for semi-supervised classifiers, as well as some functions to aid in the evaluation of these procedures.

Details

Most functions take a formula and data.frame or a matrix and factor as input and output a trained Classifier object, whose class is the class of a specific type of classifier model. predict can then be used to generate predictions for new objects, decisionvalues returns the decision values for new objects and loss outputs the loss used by the classifier evaluated on a set of new objects.

For a complete list of functions, use library(help = "RSSL").

RSSL documentation built on March 31, 2023, 7:27 p.m.