rpart model. A simplified interface to the prp function.rpart model, automatically tailoring the plot
for the model's response type.For an overview, please see the package vignette Plotting rpart trees with the rpart.plot package.
This function is a simplified front-end to prp,
with only the most useful arguments of that function, and
with different defaults for some of the arguments.
The different defaults for the extra and col.palette
arguments mean that this function automatically creates a colored plot
suitable for the type of model (whereas prp by default
creates a minimal plot). In detail the different defaults are:
| | | rpart.plot |
| | prp |
|
| | | ||||
type |
| | 2 |
||
| | | 0 |
| |
extra |
| |
"auto" |
| | 0 |
| |
fallen.leaves |
| | | TRUE |
| | FALSE |
| |
varlen |
| | 0 |
| | -8 |
| | |
faclen |
| | 0 |
| |
3 |
| |
box.palette |
| | "auto" |
| | | 0 |
| | | |
The function rpart.plot.version1 is compatible with
old versions of this function and has the same defaults as prp.
rpart.plot(x=stop("no 'x' arg"), type=2, extra="auto", under=FALSE, fallen.leaves=TRUE, digits=2, varlen=0, faclen=0, cex=NULL, tweak=1, snip=FALSE, box.palette="auto", shadow.col=0, ...)rpart object. The only required argument.
0 Draw a split label at each split and a node label at each leaf.
1 Label all nodes, not just leaves.
Similar to text.rpart's all=TRUE.
2 Default.
Like 1 but draw the split labels below the node labels.
Similar to the plots in the CART book.
3 Draw separate split labels for the left and right directions.
4 Like 3 but label all nodes, not just leaves.
Similar to text.rpart's fancy=TRUE.
See also clip.right.labs.
"auto" (case insensitive) Default.
Automatically select a value based on the model type, as follows:
extra=106 class model with a binary response
extra=104 class model with a response having more than two levels
extra=100 other models
0 No extra information.
1 Display the number of observations that fall in the node
(per class for class objects;
prefixed by the number of events for poisson and exp models).
Similar to text.rpart's use.n=TRUE.
2 Class models: display the classification rate at the node, expressed as the number of correct classifications and the number of observations in the node. Poisson and exp models: display the number of events.
3 Class models: misclassification rate at the node, expressed as the number of incorrect classifications and the number of observations in the node.
4 Class models: probability per class of observations in the node (conditioned on the node, sum across a node is 1).
5 Class models:
like 4 but do not display the fitted class.
6 Class models: the probability of the second class only. Useful for binary responses.
7 Class models:
like 6 but do not display the fitted class.
8 Class models: the probability of the fitted class.
9 Class models: the probabilities times the fraction of observations in the node (the probability relative to all observations, sum across all leaves is 1).
+100 Add 100 to any of the above to also display
the percentage of observations in the node.
For example extra=101 displays the number
and percentage of observations in the node.
Actually, it's a weighted percentage
using the weights passed to rpart.
Note 1: Unlike text.rpart,
by default prp uses its own routine for
generating node labels (not the function attached to the object).
See the node.fun argument of prp.
Note 2: The extra argument has special meaning
for mvpart objects.
See the Appendix to this package's vignette.
extra > 0.
Default FALSE, meaning put the extra text in the box.
Use TRUE to put the text under the box.
TRUE to position the leaf nodes at the bottom of the graph.
It can be helpful to use FALSE if the graph is too crowded
and the text size is too small.
2.
If 0, use getOption("digits").
Details:
Numbers from 0.001 to 9999 are printed without an exponent
(and the number of digits is actually only a suggestion,
see format for details).
Numbers out that range are printed with an ``engineering'' exponent (a multiple of 3).
0, meaning display the full variable names.
Possible values:0 use full names (default).
greater than 0 call abbreviate with the given varlen.
less than 0 truncate variable names to the shortest length where they are still unique,
but never truncate to shorter than abs(varlen).
0, meaning display the full factor names.
Possible values are as varlen above, except that
for back-compatibility with text.rpart the special value 1
means represent the factor levels with alphabetic characters
(a for the first level, b for the second, etc.).
NULL, meaning calculate the text size automatically.
cex.
Default 1, meaning no adjustment.
Use say tweak=1.2 to make the text 20% larger.
However, since font sizes are discrete the cex you ask for
may not be exactly the cex you get.
And a small change to tweak may not actually change the type size,
or change it more than you want.
FALSE.
Set TRUE to interactively trim the tree with the mouse.
See the package vignette (or just try it).
colors,
for example box.palette=c("green", "green2", "green4").
Small fitted values are displayed with colors at the start of the vector;
large values with colors at the end.The special value box.palette=0 (default for prp) uses
the background color (typically white).
The special value box.palette="auto" (default for
rpart.plot, case insensitive) automatically selects a
predefined palette based on the type of model.
Otherwise specify a predefined palette
e.g. box.palette="Grays" for the predefined gray palette (a range of grays).
The predefined palettes are (see the show.prp.palettes function):
Grays Greys Greens Blues Browns Oranges Reds Purples
Gy Gn Bu Bn Or Rd Pu (alternative names for the above palettes)
BuGn GnRd BuOr etc. (two-color diverging palettes: any combination of two of the above palettes)
RdYlGn GnYlRd (three color palettes)
Prefix the palette name with "-" to reverse the order of the colors
e.g. box.palette="-auto" or box.palette="-Grays".
0, no shadow.
Try "gray" or "darkgray".
prp.
prp
rpart.plot.version1
Functions in the rpart package:
plot.rpart
text.rpart
rpart
old.par <- par(mfrow=c(2,2)) # put 4 figures on one page
data(ptitanic)
#---------------------------------------------------------------------------
binary.model <- rpart(survived ~ ., data=ptitanic, cp=.02)
# cp=.02 for small demo tree
rpart.plot(binary.model,
main="titanic survived\n(binary response)")
rpart.plot(binary.model,
box.palette="Grays", # override default GnBu palette
main="titanic survived\nbox.palette = \"Grays\"")
#---------------------------------------------------------------------------
anova.model <- rpart(Mileage ~ ., data=cu.summary)
rpart.plot(anova.model,
shadow.col="gray", # add shadows just for kicks
main="miles per gallon\n(continuous response)\n")
#---------------------------------------------------------------------------
multi.class.model <- rpart(Reliability ~ ., data=cu.summary)
rpart.plot(multi.class.model,
main="vehicle reliability\n(multi class response)")
par(old.par)
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