gbm.effectplot: GBM plot of main effects with data distribution overlay.

In roywilsonLinc/gbmFns: Functions to enhance gbm analyses and reporting

Description

gbm.effectplot plots marginal effect for important variables.

Usage

gbm.effectplot(gbm.model, relimp.range, y.label, num.row, num.col)

Arguments

gbm.model	A gbm model to be plotted.
relimp.range	A vector of length 2 giving upper and lower relative importance cut-offs
y.label	name of response variable
num.row	Number of rows in output plot
num.col	Number of columns in output plot

Value

plot of main effects of gbm model.

Examples

## Not run: 
gbm.effectplot(gbm.model=gbm.model,
relimp.range=c(1,100),num.row=4,num.col=4)

## End(Not run)

roywilsonLinc/gbmFns documentation built on May 27, 2019, 11:47 p.m.