plot {icrf} | R Documentation |
icrf IMSE rate plot
Description
'Plot the error rates or MSE of a randomForest object'
(Quoted statements are from
randomForest
by Liaw and Wiener unless otherwise mentioned.)
Usage
## S3 method for class 'icrf'
plot(x, type = "l", main = deparse(substitute(x)), oob = FALSE, ...)
Arguments
x |
an object of |
type |
'type of plot.' |
main |
'main title of the plot.' |
oob |
Whether the out-of-bag error should be returned? |
... |
'other graphical parameters.' |
Value
The IMSE (integrated mean squared error) of the icrf
object
is invisibly returned. 'If the object has a non-null test component, then the returned
object is a matrix where the first' (two) column is the IMSE measure (types 1 and 2), 'and
the second column is for the test set.'
The rows represent the forest iterations.
Note
'If the x
has a non-null test
component, then the test set errors are
also plotted.'
Author(s)
Hunyong Cho, Nicholas P. Jewell, and Michael R. Kosorok.
References
Cho H., Jewell N. J., and Kosorok M. R. (2020+). "Interval censored recursive forests"
Examples
# rats data example
# Note that this is a toy example. Use a larger ntree and nfold in practice.
data(rat2)
set.seed(1)
samp <- sample(1:dim(rat2)[1], 200)
rats.train <- rat2[samp, ]
rats.test <- rat2[-samp, ]
# Note that this is a toy example. Use a larger ntree and nfold in practice.
set.seed(2)
rats.icrf.small <-
icrf(~ dose.lvl + weight + male + cage.no, data = rat2,
data.type = "currentstatus", currentstatus.label = c("survtime", "tumor"),
returnBest = TRUE, ntree=10, nfold=3)
plot(rats.icrf.small)