1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
|
#' @export
makeRLearner.regr.fnn = function() {
makeRLearnerRegr(
cl = "regr.fnn",
package = "FNN",
# l is for reject option. cannot be done with mlr atm
par.set = makeParamSet(
makeIntegerLearnerParam(id = "k", default = 3L, lower = 1L),
makeDiscreteLearnerParam(id = "algorithm", default = "cover_tree",
values = list("kd_tree", "cover_tree", "brute"))
),
properties = "numerics",
name = "Fast k-Nearest Neighbor",
short.name = "fnn",
callees = "knn.reg"
)
}
#' @export
trainLearner.regr.fnn = function(.learner, .task, .subset, .weights = NULL, ...) {
d = getTaskData(.task, .subset, target.extra = TRUE)
list(train = d, parset = list(...))
}
#' @export
predictLearner.regr.fnn = function(.learner, .model, .newdata, ...) {
m = .model$learner.model
pars = c(list(train = m$train$data, test = .newdata, y = m$train$target), m$parset, list(...))
do.call(FNN::knn.reg, pars)$pred
}
|
