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#' @export
makeRLearner.classif.OneR = function() {
makeRLearnerClassif(
cl = "classif.OneR",
package = "RWeka",
par.set = makeParamSet(
makeIntegerLearnerParam(id = "B", default = 6L, lower = 1L),
makeLogicalLearnerParam(id = "output-debug-info", default = FALSE, tunable = FALSE)
),
properties = c("twoclass", "multiclass", "missings", "numerics", "factors", "prob"),
name = "1-R Classifier",
short.name = "oner",
note = "NAs are directly passed to WEKA with `na.action = na.pass`.",
callees = c("OneR", "Weka_control")
)
}
#' @export
trainLearner.classif.OneR = function(.learner, .task, .subset, .weights = NULL, ...) {
f = getTaskFormula(.task)
ctrl = RWeka::Weka_control(...)
RWeka::OneR(f, data = getTaskData(.task, .subset), control = ctrl, na.action = na.pass)
}
#' @export
predictLearner.classif.OneR = function(.learner, .model, .newdata, ...) {
type = switch(.learner$predict.type, prob = "prob", "class")
predict(.model$learner.model, newdata = .newdata, type = type, ...)
}
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