oob_predictions: Out-of-bag predictions for a random forest.

In ppforest2: Projection Pursuit Oblique Decision Trees and Random Forests

Out-of-bag predictions for a random forest.

Description

Returns predictions for each training row using only trees that did not see that row in their bootstrap sample. Observations with no OOB tree are represented as 'NA' in both modes: 'NA' at the factor level for classification, and 'NA_real_' for regression. Filter with the standard 'is.na()' idiom.

Usage

oob_predictions(model)

Arguments

model

A pprf forest model.

Value

A factor (classification) or numeric vector (regression), length 'n'.

See Also

oob_error, oob_samples

ppforest2 documentation built on July 21, 2026, 9:07 a.m.