randomUniformForest (version 1.1.6)

rUniformForest.grow: Add trees to a random Uniform Forest

Description

add more trees to the ensemble model

Usage

rUniformForest.grow(object, X, Y = NULL, ntree = 100, threads = "auto")

Arguments

object

an object of class randomUniformForest.

X

current matrix or data frame used to compute 'object' model. One can also choose another matrix with same features and appropriate training responses (see below). All parameters will still remain. To combine heterogeneous models, use randomUniformForest.combine() function.

Y

vector of training reponses, if one wants to add trees with another matrix (with same features, but different observations). Otherwise, let it to NULL if same model has to be computed on same data.

ntree

number of trees to add to the model.

threads

compute model in parallel for computers with many cores. Default value is "auto", letting model running on all logical cores minus 1. User can set 'threads' to any values >= 1, depending on the number of cores (including logical).

Value

an object of class randomUniformForest, containing new and old trees.

Details

rUniformForest.grow allows both to add new trees or new model (by adding trees on a new matrix and training responses) built on the same bases than the former. Note that with formula, only new trees can be added, not new model.

See Also

rUniformForest.big, rUniformForest.combine

Examples

# NOT RUN {
# data(iris)
# iris.rf <- randomUniformForest(Species ~ ., iris, ntree = 50, threads = 1, BreimanBounds = FALSE)
# iris.rf <- rUniformForest.grow(iris.rf, iris, ntree = 20, threads = 1)
# iris.rf
# }