Plot the predicted response from a gg_rfsrc object, the
rfsrc prediction, using the OOB prediction
from the forest.
Usage
# S3 method for class 'gg_rfsrc'
plot(x, ...)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.
Examples
## ------------------------------------------------------------
## classification example
## ------------------------------------------------------------
## -------- iris data
# Build a small classification forest (ntree=50 keeps example fast)
set.seed(42)
rfsrc_iris <- rfsrc(Species ~ ., data = iris, ntree = 50)
gg_dta <- gg_rfsrc(rfsrc_iris)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 450 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
## ------------------------------------------------------------
## Regression example
## ------------------------------------------------------------
## -------- air quality data
# na.action = "na.impute" handles missing Ozone / Solar.R values
set.seed(42)
rfsrc_airq <- rfsrc(Ozone ~ ., data = airquality,
na.action = "na.impute", ntree = 50)
gg_dta <- gg_rfsrc(rfsrc_airq)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 153 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
#> Warning: All aesthetics have length 1, but the data has 153 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
## -------- mtcars data
set.seed(42)
rfsrc_mtcars <- rfsrc(mpg ~ ., data = mtcars, ntree = 50)
gg_dta <- gg_rfsrc(rfsrc_mtcars)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 32 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
#> Warning: All aesthetics have length 1, but the data has 32 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
## ------------------------------------------------------------
## Survival example
## ------------------------------------------------------------
## -------- veteran data
## randomized trial of two treatment regimens for lung cancer
data(veteran, package = "randomForestSRC")
set.seed(42)
rfsrc_veteran <- rfsrc(Surv(time, status) ~ ., data = veteran, ntree = 50)
gg_dta <- gg_rfsrc(rfsrc_veteran)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 13289 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
# With 95% pointwise bootstrap confidence bands
gg_dta <- gg_rfsrc(rfsrc_veteran, conf.int = .95)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 97 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
#> Warning: All aesthetics have length 1, but the data has 97 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
# Stratified by treatment arm
gg_dta <- gg_rfsrc(rfsrc_veteran, by = "trt")
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 194 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
#> Warning: All aesthetics have length 1, but the data has 194 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
## -------- pbc data (larger dataset -- skipped on CRAN)
# \donttest{
data(pbc, package = "randomForestSRC")
# For whatever reason, the age variable is in days; convert to years
for (ind in seq_len(dim(pbc)[2])) {
if (!is.factor(pbc[, ind])) {
if (length(unique(pbc[which(!is.na(pbc[, ind])), ind])) <= 2) {
if (sum(range(pbc[, ind], na.rm = TRUE) == c(0, 1)) == 2) {
pbc[, ind] <- as.logical(pbc[, ind])
}
}
} else {
if (length(unique(pbc[which(!is.na(pbc[, ind])), ind])) <= 2) {
if (sum(sort(unique(pbc[, ind])) == c(0, 1)) == 2) {
pbc[, ind] <- as.logical(pbc[, ind])
}
if (sum(sort(unique(pbc[, ind])) == c(FALSE, TRUE)) == 2) {
pbc[, ind] <- as.logical(pbc[, ind])
}
}
}
if (!is.logical(pbc[, ind]) &
length(unique(pbc[which(!is.na(pbc[, ind])), ind])) <= 5) {
pbc[, ind] <- factor(pbc[, ind])
}
}
# Convert age from days to years
pbc$age <- pbc$age / 364.24
pbc$years <- pbc$days / 364.24
pbc <- pbc[, -which(colnames(pbc) == "days")]
pbc$treatment <- as.numeric(pbc$treatment)
pbc$treatment[which(pbc$treatment == 1)] <- "DPCA"
pbc$treatment[which(pbc$treatment == 2)] <- "placebo"
pbc$treatment <- factor(pbc$treatment)
# Remove test-set patients (those with no assigned treatment)
dta_train <- pbc[-which(is.na(pbc$treatment)), ]
set.seed(42)
rfsrc_pbc <- randomForestSRC::rfsrc(
Surv(years, status) ~ .,
dta_train,
nsplit = 10,
na.action = "na.impute",
forest = TRUE,
importance = TRUE,
save.memory = TRUE
)
gg_dta <- gg_rfsrc(rfsrc_pbc)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 38064 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
gg_dta <- gg_rfsrc(rfsrc_pbc, conf.int = .95)
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 122 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
#> Warning: All aesthetics have length 1, but the data has 122 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
gg_dta <- gg_rfsrc(rfsrc_pbc, by = "treatment")
plot(gg_dta)
#> Warning: All aesthetics have length 1, but the data has 244 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
#> Warning: All aesthetics have length 1, but the data has 244 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#> a single row.
# }