riAFTBART (version 0.3.2)

intree: Interpreting Tree Ensembles with inTrees

Description

The inTrees (interpretable trees) framework that extracts, measures, prunes and selects rules from a tree ensemble. All the codes we use are from the inTrees github repository to act as a work around method since package inTrees was removed from the CRAN repository.

Usage

intree(X, Y, ntree, typeDecay = 2, digits, n_rule)

Arguments

X

A matrix indicating the predictor variables.

Y

A response vector. If a factor, classification is assumed, otherwise regression is assumed.

ntree

Number of trees to grow. This should not be set to too small a number, to ensure that every input row gets predicted at least a few times.

typeDecay

An integer of 1 or 2. 1 representing relative error and 2 representing error. The default is set to 2.

digits

An integer indicating the digits for rounding in Intrees.

n_rule

An integer indicating the minimum number of rules to consider in Intrees.

Value

A matrix including a set of relevant and non-redundant rules, and their metrics

Examples

# NOT RUN {
X <- within(iris,rm("Species")); Y <- iris[,"Species"]
intree_result <- intree(X, Y, ntree=100, digits = 3, n_rule = 2000)


# }