predict.WellSVMSSLR

object

<p>This parameter is included for compatibility reasons.</p>

Providing a collection of techniques for semi-supervised
classification and regression. In semi-supervised problem, both labeled and unlabeled
data are used to train a classifier. The package includes a collection of
semi-supervised learning techniques: self-training, co-training, democratic,
decision tree, random forest, 'S3VM' ... etc, with a fairly intuitive interface
that is easy to use.

Francisco Jes<c3><ba>s Palomares Alabarce

SSLR

Semi-Supervised Classification and Regression Methods

Jos<c3><a9> Manuel Ben<c3><ad>tez

Isaac Triguero

Christoph Bergmeir

Mabel Gonz<c3><a1>lez

predict.WellSVMSSLR function

Predict WellSVMSSLR — predict.WellSVMSSLR

Predict WellSVMSSLR

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predict.WellSVMSSLR: Predict WellSVMSSLR

Description

Usage

Arguments