grf (version 0.9.4)

predict.custom_forest: Predict with a custom forest.

Description

Predict with a custom forest.

Usage

# S3 method for custom_forest
predict(object, newdata = NULL, num.threads = NULL,
  ...)

Arguments

object

The trained forest.

newdata

Points at which predictions should be made. If NULL, makes out-of-bag predictions on the training set instead (i.e., provides predictions at Xi using only trees that did not use the i-th training example).

num.threads

Number of threads used in training. If set to NULL, the software automatically selects an appropriate amount.

...

Additional arguments (currently ignored).

Value

Vector of predictions.

Examples

# NOT RUN {
# Train a custom forest.
n = 50; p = 10
X = matrix(rnorm(n*p), n, p)
Y = X[,1] * rnorm(n)
c.forest = custom_forest(X, Y)

# Predict using the forest.
X.test = matrix(0, 101, p)
X.test[,1] = seq(-2, 2, length.out = 101)
c.pred = predict(c.forest, X.test)

# }