mlr (version 2.7)

makeClassifTask: Create a classification, regression, survival, cluster, cost-sensitive classification or multilabel task.

Description

The task encapsulates the data and specifies - through its subclasses - the type of the task. It also contains a description object detailing further aspects of the data.

Useful operators are: getTaskFormula, getTaskFeatureNames, getTaskData, getTaskTargets, and subsetTask.

Object members: [object Object],[object Object],[object Object],[object Object]

Notes: For multilabel classification we assume that the presence of labels is encoded via logical columns in data. The name of the column specifies the name of the label. target is then a char vector that points to these columns.

Usage

makeClassifTask(id = deparse(substitute(data)), data, target,
  weights = NULL, blocking = NULL, positive = NA_character_,
  fixup.data = "warn", check.data = TRUE)
makeClusterTask(id = deparse(substitute(data)), data, weights = NULL,
  blocking = NULL, fixup.data = "warn", check.data = TRUE)
makeCostSensTask(id = deparse(substitute(data)), data, costs,
  blocking = NULL, fixup.data = "warn", check.data = TRUE)
makeMultilabelTask(id = deparse(substitute(data)), data, target,
  weights = NULL, blocking = NULL, positive = NA_character_,
  fixup.data = "warn", check.data = TRUE)
makeRegrTask(id = deparse(substitute(data)), data, target, weights = NULL,
  blocking = NULL, fixup.data = "warn", check.data = TRUE)
makeSurvTask(id = deparse(substitute(data)), data, target,
  censoring = "rcens", weights = NULL, blocking = NULL,
  fixup.data = "warn", check.data = TRUE)

Value

[Task].

See Also

Other costsens: makeCostSensClassifWrapper, makeCostSensRegrWrapper, makeCostSensWeightedPairsWrapper

Examples

library(mlbench)
data(BostonHousing)
data(Ionosphere)

makeClassifTask(data = iris, target = "Species")
makeRegrTask(data = BostonHousing, target = "medv")
# an example of a classification task with more than those standard arguments:
blocking = factor(c(rep(1, 51), rep(2, 300)))
makeClassifTask(id = "myIonosphere", data = Ionosphere, target = "Class",
  positive = "good", blocking = blocking)
makeClusterTask(data = iris[, -5L])