R: Plot the Partitions of a simple Tree Model

partition.tree {tree} | R Documentation

## Plot the Partitions of a simple Tree Model

### Description

Plot the partitions of a tree involving one or two variables.

### Usage

    partition.tree(tree, label = "yval", add = FALSE, ordvars, ...)

### Arguments

`tree` | A object of class `"tree"`.
`label` | A character string giving the column of the frame component of `tree` to be used to label the regions.
`add` | If true, add to existing plot, otherwise start a new plot.
`ordvars` | The ordering of the variables to be used in a 2D plot. Specify the names in a character string of length 2; the first will be used on the `x` axis.
`...` | Graphical parameters.

### Details

This can be used with a regression or classification tree containing one or two continuous predictors (only).

If the tree contains one predictor, the predicted value (a regression tree) or the probability of the first class (a classification tree) is plotted against the predictor over its range in the training set.

If the tree contains two predictors, a plot is made of the space covered by those two predictors and the partition made by the tree is superimposed.

### Value

None.

### Author(s)

B. D. Ripley

### See Also

`tree`

### Examples

    ir.tr <- tree(Species ~., iris)
    ir.tr
    ir.tr1 <- snip.tree(ir.tr, nodes = c(12, 7))
    summary(ir.tr1)
    par(pty = "s")
    plot(iris[, 3],iris[, 4], type="n",
         xlab="petal length", ylab="petal width")
    text(iris[, 3], iris[, 4], c("s", "c", "v")[iris[, 5]])
    partition.tree(ir.tr1, add = TRUE, cex = 1.5)

    # 1D example
    ir.tr <- tree(Petal.Width ~ Petal.Length, iris)
    plot(iris[,3], iris[,4], type="n", xlab="Length", ylab="Width")
    partition.tree(ir.tr, add = TRUE, cex = 1.5)

[Package tree version 1.0-39 Index]