gbm_2way: Two-way interactions

In bgreenwell/treemisc: Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R"

Two-way interactions

Description

Computes Friedman's H-statistic (Friedman & Popescu, 2008) for all pairwise interaction effects in a gbm model.

Usage

gbm_2way(object, data, var.names = object$var.names, n.trees = object$n.trees)

Arguments

object	A gbm object.
data	Data frame containing the original training data (or representative sample thereof).
var.names	Character string specifying the predictor names to consider.
n.trees	Integer specifying the number of trees to use.

Value

A data frame with the following three columns:

var1

The name of the first feature.

var2

The name of the second feature.

h

The corresponding H-statistic.

The resulting rows are sorted in descending order of h.

References

Friedman, J. H., & Popescu, B. E. (2008). Predictive Learning via Rule Ensembles. The Annals of Applied Statistics, 2(3), 916–954. http://www.jstor.org/stable/30245114

bgreenwell/treemisc documentation built on Oct. 26, 2022, 12:56 a.m.