BaselearnerCategoricalBinary: Base learner to encode one single class of a categorical...
| BaselearnerCategoricalBinary | R Documentation |
Base learner to encode one single class of a categorical feature
Description
This class create a one-column one-hot encoded data matrix with ones at
x == class_name and zero otherwise.
Arguments
data_source |
CategoricalDataRaw |
class_name |
( |
blearner_type |
( |
Format
S4 object.
Usage
BaselearnerCategoricalBinary$new(data_source, class_name) BaselearnerCategoricalBinary$new(data_source, class_name, blearner_type)
Fields
This class doesn't contain public fields.
Methods
-
$summarizeFactory():() -> () -
$transfromData(newdata):list(InMemoryData) -> matrix() -
$getMeta():() -> list()
Inherited methods from Baselearner
-
$getData():() -> matrix() -
$getDF():() -> integer() -
$getPenalty():() -> numeric() -
$getPenaltyMat():() -> matrix() -
$getFeatureName():() -> character() -
$getModelName():() -> character() -
$getBaselearnerId():() -> character()
Examples
# Sample data:
x = sample(c("one","two"), 20, TRUE)
y = c(one = 0.8, two = -1.2)[x] + rnorm(20, 0, 0.2)
dat = data.frame(x, y)
# S4 API:
ds = CategoricalDataRaw$new(x, "cat")
bl = BaselearnerCategoricalBinary$new(ds, "one")
bl$getData()
bl$summarizeFactory()
bl$transformData(list(ds))
bl$getBaselearnerId()
# R6 API:
cboost = Compboost$new(dat, "y")
cboost$addBaselearner("x", "binary", BaselearnerCategoricalBinary)
cboost$train(500, 0)
table(cboost$getSelectedBaselearner())
plotPEUni(cboost, "x", individual = FALSE)
