#' @title Cobweb Clustering Learner
#'
#' @name mlr_learners_clust.cobweb
#'
#' @description
#' A [LearnerClust] for Cobweb clustering implemented in [RWeka::Cobweb()].
#' The predict method uses [RWeka::predict.Weka_clusterer()] to compute the
#' cluster memberships for new data.
#'
#' @templateVar id clust.cobweb
#' @template learner
#'
#' @references
#' `r format_bib("witten2002data", "fisher1987knowledge", "gennari1989models")`
#'
#' @export
#' @template seealso_learner
#' @template example
LearnerClustCobweb = R6Class("LearnerClustCobweb",
inherit = LearnerClust,
public = list(
#' @description
#' Creates a new instance of this [R6][R6::R6Class] class.
initialize = function() {
param_set = ps(
A = p_dbl(0, default = 1, tags = "train"),
C = p_dbl(0, default = 0.002, tags = "train"),
S = p_int(1L, default = 42L, tags = "train")
)
super$initialize(
id = "clust.cobweb",
feature_types = c("logical", "integer", "numeric"),
predict_types = "partition",
param_set = param_set,
properties = c("partitional", "exclusive", "complete"),
packages = "RWeka",
man = "mlr3cluster::mlr_learners_clust.cobweb",
label = "Cobweb Clustering"
)
}
),
private = list(
.train = function(task) {
pv = self$param_set$get_values(tags = "train")
ctrl = invoke(RWeka::Weka_control, .args = pv)
m = invoke(RWeka::Cobweb, x = task$data(), control = ctrl)
if (self$save_assignments) {
self$assignments = unname(m$class_ids + 1L)
}
m
},
.predict = function(task) {
partition = invoke(predict, self$model, newdata = task$data(), type = "class") + 1L
PredictionClust$new(task = task, partition = partition)
}
)
)
#' @include zzz.R
register_learner("clust.cobweb", LearnerClustCobweb)
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