LearnerSurvRangerCox {mlsurvlrnrs} | R Documentation |
The 'LearnerSurvRangerCox' class is the interface to perform a Cox regression with the 'ranger' R package for use with the 'mlexperiments' package.
Optimization metric: C-index Can be used with * [mlexperiments::MLTuneParameters] * [mlexperiments::MLCrossValidation] * [mlexperiments::MLNestedCVs]
mlexperiments::MLLearnerBase
-> LearnerSurvRangerCox
new()
Create a new 'LearnerSurvRangerCox' object.
LearnerSurvRangerCox$new()
A new 'LearnerSurvRangerCox' R6 object.
LearnerSurvRangerCox$new()
clone()
The objects of this class are cloneable with this method.
LearnerSurvRangerCox$clone(deep = FALSE)
deep
Whether to make a deep clone.
[ranger::ranger()]
# survival analysis
dataset <- survival::colon |>
data.table::as.data.table() |>
na.omit()
dataset <- dataset[get("etype") == 2, ]
seed <- 123
surv_cols <- c("status", "time", "rx")
feature_cols <- colnames(dataset)[3:(ncol(dataset) - 1)]
param_list_ranger <- expand.grid(
sample.fraction = seq(0.6, 1, .2),
min.node.size = seq(1, 5, 4),
mtry = seq(2, 6, 2),
num.trees = c(5L, 10L),
max.depth = seq(1, 5, 4)
)
ncores <- 2L
split_vector <- splitTools::multi_strata(
df = dataset[, .SD, .SDcols = surv_cols],
strategy = "kmeans",
k = 4
)
train_x <- model.matrix(
~ -1 + .,
dataset[, .SD, .SDcols = setdiff(feature_cols, surv_cols[1:2])]
)
train_y <- survival::Surv(
event = (dataset[, get("status")] |>
as.character() |>
as.integer()),
time = dataset[, get("time")],
type = "right"
)
fold_list <- splitTools::create_folds(
y = split_vector,
k = 3,
type = "stratified",
seed = seed
)
surv_ranger_cox_optimizer <- mlexperiments::MLCrossValidation$new(
learner = LearnerSurvRangerCox$new(),
fold_list = fold_list,
ncores = ncores,
seed = seed
)
surv_ranger_cox_optimizer$learner_args <- as.list(
data.table::data.table(param_list_ranger[1, ], stringsAsFactors = FALSE)
)
surv_ranger_cox_optimizer$performance_metric <- c_index
# set data
surv_ranger_cox_optimizer$set_data(
x = train_x,
y = train_y
)
surv_ranger_cox_optimizer$execute()
## ------------------------------------------------
## Method `LearnerSurvRangerCox$new`
## ------------------------------------------------
LearnerSurvRangerCox$new()