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#' @title Create a classification task.
#' @inheritParams Task
#' @seealso [Task] [CostSensTask] [ClusterTask] [MultilabelTask] [RegrTask] [SurvTask]
#' @rdname ClassifTask
#' @aliases ClassifTask
#' @export
makeClassifTask = function(id = deparse(substitute(data)), data, target, weights = NULL, blocking = NULL, coordinates = NULL, positive = NA_character_, fixup.data = "warn", check.data = TRUE) {
assertString(id)
assertDataFrame(data)
assertString(target)
# some code on cran passed stuff like positive=1, we can live with the convert here
if (isScalarNumeric(positive)) {
positive = as.character(positive)
}
assertString(positive, na.ok = TRUE)
assertChoice(fixup.data, choices = c("no", "quiet", "warn"))
assertFlag(check.data)
if (fixup.data != "no") {
x = data[[target]]
if (is.character(x) || is.logical(x) || is.integer(x)) {
data[[target]] = as.factor(x)
} else if (is.factor(x) && fixup.data == "warn" && hasEmptyLevels(x)) {
warningf("Target column '%s' contains empty factor levels", target)
data[[target]] = droplevels(x)
}
}
task = makeSupervisedTask("classif", data, target, weights, blocking, coordinates, fixup.data = fixup.data, check.data = check.data)
if (check.data) {
assertFactor(data[[target]], any.missing = FALSE, empty.levels.ok = FALSE, .var.name = target)
}
task$task.desc = makeClassifTaskDesc(id, data, target, weights, blocking, positive, coordinates)
addClasses(task, "ClassifTask")
}
#' @export
#' @rdname makeTaskDesc
makeClassifTaskDesc = function(id, data, target, weights, blocking, positive, coordinates) {
levs = levels(data[[target]])
m = length(levs)
if (is.na(positive)) {
if (m <= 2L) {
positive = levs[1L]
}
} else {
if (m > 2L) {
stop("Cannot set a positive class for a multiclass problem!")
}
assertChoice(positive, choices = levs)
}
td = makeTaskDescInternal("classif", id, data, target, weights, blocking, coordinates)
td$class.levels = levs
td$positive = positive
td$negative = NA_character_
td$class.distribution = table(data[target], dnn = "")
if (length(td$class.levels) == 1L) {
td$negative = stri_paste("not_", positive)
} else if (length(td$class.levels) == 2L) {
td$negative = setdiff(td$class.levels, positive)
}
return(addClasses(td, c("ClassifTaskDesc", "SupervisedTaskDesc")))
}
#' @export
print.ClassifTask = function(x, ...) {
di = printToChar(x$task.desc$class.distribution)
m = length(x$task.desc$class.levels)
print.SupervisedTask(x)
catf("Classes: %i", m, newline = FALSE)
# remove 1st newline
cat(di)
catf("\nPositive class: %s", x$task.desc$positive)
}
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