predict.rf_classifier: Predict Class Labels using a Random Forest Classifier Object

In bbuchsbaum/multivarious: Extensible Data Structures for Multivariate Analysis

Predict Class Labels using a Random Forest Classifier Object

Description

Predicts class labels and probabilities for new data using a fitted rf_classifier object. This method projects the new_data into the component space and then uses the stored randomForest model to predict outcomes.

Usage

## S3 method for class 'rf_classifier'
predict(object, new_data, ncomp = NULL, colind = NULL, ...)

Arguments

object	A fitted object of class rf_classifier.
new_data	A numeric matrix or vector of new observations to classify. Rows are observations, columns are variables matching the original data space used by the projector OR matching colind if provided.
ncomp	Optional integer; the number of components to use from the projector for classification (default: all components used during classifier creation).
colind	Optional numeric vector specifying column indices from the original data space. If provided, new_data is projected using only these features (partial_project). This overrides any colind stored default in the object. The resulting projection is compared against the reference scores (object$scores) stored in the classifier.
...	Extra arguments passed to predict.randomForest.

Value

A list containing:

class	Predicted class labels (typically factor) from the random forest model.
prob	A numeric matrix of predicted class probabilities from the random forest model.

See Also

rf_classifier.projector, predict.randomForest

Other classifier predict: predict.classifier()

bbuchsbaum/multivarious documentation built on July 16, 2025, 11:04 p.m.