ggRandomForests (version 2.2.0)

gg_error: randomForest error rate data object

Description

Extract the cumulative (OOB) randomForestSRC error rate as a function of number of trees.

Usage

gg_error(object, ...)

Value

gg_error

data.frame with one column indicating the tree number, and the remaining columns from the rfsrc$err.rate return value.

Arguments

object

rfsrc object.

...

optional arguments (not used).

Details

The gg_error function simply returns the rfsrc$err.rate object as a data.frame, and assigns the class for connecting to the S3 plot.gg_error function.

References

Breiman L. (2001). Random forests, Machine Learning, 45:5-32.

Ishwaran H. and Kogalur U.B. (2007). Random survival forests for R, Rnews, 7(2):25-31.

Ishwaran H. and Kogalur U.B. (2013). Random Forests for Survival, Regression and Classification (RF-SRC), R package version 1.4.

See Also

plot.gg_error rfsrc plot.rfsrc

Examples

## Examples from RFSRC package...
## ------------------------------------------------------------
## classification example
## ------------------------------------------------------------
## ------------- iris data
## You can build a randomForest
# rfsrc_iris <- rfsrc(Species ~ ., data = iris)
# ... or load a cached randomForestSRC object
data(rfsrc_iris, package="ggRandomForests")

# Get a data.frame containing error rates
gg_dta<- gg_error(rfsrc_iris)

# Plot the gg_error object
plot(gg_dta)

## RandomForest example
rf_iris <- randomForest::randomForest(Species ~ ., data = iris)
gg_dta <- gg_error(rf_iris)
plot(gg_dta)

gg_dta <- gg_error(rf_iris, training=TRUE)
plot(gg_dta)
## ------------------------------------------------------------
## Regression example
## ------------------------------------------------------------
if (FALSE) {
## ------------- airq data
rfsrc_airq <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")

# Get a data.frame containing error rates
gg_dta<- gg_error(rfsrc_airq)

# Plot the gg_error object
plot(gg_dta)
}

## ------------- Boston data
data(rfsrc_boston, package="ggRandomForests")

# Get a data.frame containing error rates
gg_dta<- gg_error(rfsrc_boston)

# Plot the gg_error object
plot(gg_dta)

if (FALSE) {
## ------------- mtcars data

# Get a data.frame containing error rates
gg_dta<- gg_error(rfsrc_mtcars)

# Plot the gg_error object
plot(gg_dta)
}

## ------------------------------------------------------------
## Survival example
## ------------------------------------------------------------
if (FALSE) {
## ------------- veteran data
## randomized trial of two treatment regimens for lung cancer
data(veteran, package = "randomForestSRC")
rfsrc_veteran <- rfsrc(Surv(time, status) ~ ., data = dta$veteran, ...)

gg_dta <- gg_error(rfsrc_veteran)
plot(gg_dta)

## ------------- pbc data
# Load a cached randomForestSRC object
data(rfsrc_pbc, package="ggRandomForests")

gg_dta <- gg_error(rfsrc_pbc)
plot(gg_dta)
}