plot.logicDT: Plot a logic decision tree

In logicDT: Identifying Interactions Between Binary Predictors

Plot a logic decision tree

Description

This function plots a logicDT model on the active graphics device.

Usage

fancy.plot(x, ...)

## S3 method for class 'logicDT'
plot(x, fancy = TRUE, x_scaler = 0.5, margin_scaler = 0.2, cex = 1, ...)

Arguments

x	An object of the class logicDT
...	Arguments passed to fancy plotting function
fancy	Should the fancy mode be used for plotting? Default is TRUE.
x_scaler	Scaling factor on the horizontal axis for deeper trees, i.e., x_scaler = 0.5 means that the horizontal distance between two adjacent nodes is halved for every vertical level.
margin_scaler	Margin factor. Smaller values lead to smaller margins.
cex	Scaling factor for the plotted text elements.

Details

There are two plotting modes:

• fancy = FALSE which draws a tree with direct edges between the nodes. Leaves are represented by their prediction value which is obtained by the (observed) conditional mean.

• fancy = TRUE plots a tree similar to those in the rpart (Therneau and Atkinson, 2019) and splinetree (Neufeld and Heggeseth, 2019) R packages. The trees are drawn in an angular manner and if 4pL modeling was used for the leaves, appropriate plots of the fitted curves are depicted in the leaves. Otherwise, the usual prediction values are shown.

Value

No return value, called for side effects

References

• Therneau, T. & Atkinson, B. (2019). rpart: Recursive Partitioning and Regression Trees. https://CRAN.R-project.org/package=rpart

• Neufeld, A. & Heggeseth, B. (2019). splinetree: Longitudinal Regression Trees and Forests. https://CRAN.R-project.org/package=splinetree

logicDT documentation built on Jan. 14, 2023, 5:06 p.m.