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#' @export
makeRLearner.regr.nodeHarvest = function() {
makeRLearnerRegr(
cl = "regr.nodeHarvest",
package = "nodeHarvest",
par.set = makeParamSet(
makeIntegerLearnerParam(id = "nodesize", default = 10L, lower = 1L),
makeIntegerLearnerParam(id = "nodes", default = 1000L, lower = 1L),
makeIntegerLearnerParam(id = "maxinter", default = 2L, lower = 1L),
makeDiscreteLearnerParam(id = "mode", default = "mean", values = c("mean", "outbag")),
makeNumericLearnerParam(id = "lambda"),
makeUntypedLearnerParam(id = "addto", default = NULL),
makeLogicalLearnerParam(id = "onlyinter"),
makeLogicalLearnerParam(id = "silent", default = FALSE, tunable = FALSE),
makeLogicalLearnerParam(id = "biascorr", default = FALSE)
),
properties = c("numerics", "factors"),
name = "Node Harvest",
short.name = "nodeHarvest",
callees = "nodeHarvest"
)
}
#' @export
trainLearner.regr.nodeHarvest = function(.learner, .task, .subset, .weights = NULL, ...) {
d = getTaskData(.task, .subset, target.extra = TRUE)
nodeHarvest::nodeHarvest(X = d$data, Y = d$target, ...)
}
#' @export
predictLearner.regr.nodeHarvest = function(.learner, .model, .newdata, ...) {
predict(.model$learner.model, .newdata, ...)
}
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