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# FIXME: probs can only be predicted for two class problems (winning class)
#' @export
makeRLearner.classif.fnn = function() {
makeRLearnerClassif(
cl = "classif.fnn",
package = "FNN",
par.set = makeParamSet(
makeIntegerLearnerParam(id = "k", default = 1L, lower = 1L),
makeLogicalLearnerParam(id = "prob", default = FALSE, tunable = FALSE),
makeDiscreteLearnerParam(id = "algorithm", default = "cover_tree",
values = list("cover_tree", "kd_tree", "brute"))
),
properties = c("twoclass", "multiclass", "numerics"),
name = "Fast k-Nearest Neighbour",
short.name = "fnn",
callees = "knn"
)
}
#' @export
trainLearner.classif.fnn = function(.learner, .task, .subset, .weights = NULL, ...) {
d = getTaskData(.task, .subset, target.extra = TRUE)
list(train = d, parset = list(...))
}
#' @export
predictLearner.classif.fnn = function(.learner, .model, .newdata, ...) {
m = .model$learner.model
pars = list(train = m$train$data, test = .newdata, cl = m$train$target)
pars = c(pars, m$parset, list(...))
p = do.call(FNN::knn, pars)
attr(p, "nn.index") = NULL
attr(p, "nn.dist") = NULL
return(p)
}
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