predict.RandomForestSemisupervised_fitted

RandomForestSemisupervised_fitted.

object

A object that can be coerced as matrix.
Depending on how was the model built, <code>x</code> is interpreted as a matrix
with the distances between the unseen instances and the selected training instances,
or a matrix of instances.

type

Is param to define the type of predict.
It can be "max_prob", to get class with sum of probability is the maximum
Or "vote" to get the most frequented class in all trees.
Default is "max_prob"

confident

This parameter is included for compatibility reasons.

Predicts the label of instances according to the RandomForestSemisupervised_fitted model.

Providing a collection of techniques for semi-supervised
classification, regression and clustering. 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.

predict.RandomForestSemisupervised_fitted: Predictions of the SSLRDecisionTree_fitted method

Description

Usage

Arguments

Value