added cobweb learner

DESCRIPTION

@@ -41,6 +41,7 @@ Collate:
     'LearnerClust.R'
     'LearnerClustAgnes.R'
     'LearnerClustCMeans.R'
+    'LearnerClustCobweb.R'
     'LearnerClustDBSCAN.R'
     'LearnerClustDiana.R'
     'LearnerClustFanny.R'

NAMESPACE

@@ -8,6 +8,7 @@ S3method(is_missing_prediction_data,PredictionDataClust)
 export(LearnerClust)
 export(LearnerClustAgnes)
 export(LearnerClustCMeans)
+export(LearnerClustCobweb)
 export(LearnerClustDBSCAN)
 export(LearnerClustDiana)
 export(LearnerClustFanny)

R/LearnerClustCobweb.R

@@ -0,0 +1,53 @@
+#' @title Cobweb Clustering Learner
+#'
+#' @name mlr_learners_clust.cobweb
+#' @include LearnerClust.R
+#'
+#' @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 section_dictionary_learner
+#' @template example
+#'
+#' @export
+LearnerClustCobweb = R6Class("LearnerClustCobweb",
+  inherit = LearnerClust,
+  public = list(
+   #' @description
+   #' Creates a new instance of this [R6][R6::R6Class] class.
+   initialize = function() {
+     ps = ParamSet$new(
+       params = list(
+         ParamDbl$new(id = "A", default = 1, lower = 0, tags = "train"),
+         ParamDbl$new(id = "C", default = 0.002, lower = 0, tags = "train"),
+         ParamInt$new(id = "S", default = 42L, lower = 1L, tags = "train")
+       )
+     )
+
+     super$initialize(
+       id = "clust.cobweb",
+       feature_types = c("logical", "integer", "numeric"),
+       predict_types = "partition",
+       param_set = ps,
+       properties = c("partitional", "exclusive", "complete"),
+       packages = "RWeka"
+     )
+   }
+  ),
+
+  private = list(
+   .train = function(task) {
+     pv = self$param_set$get_values(tags = "train")
+     ctrl = do.call(RWeka::Weka_control, pv)
+     invoke(RWeka::Cobweb, x = task$data(), control = ctrl)
+   },
+
+   .predict = function(task) {
+     partition = predict(self$model, newdata = task$data(), type = "class") + 1L
+     PredictionClust$new(task = task, partition = partition)
+   }
+  )
+)

R/zzz.R

@@ -41,6 +41,7 @@ register_mlr3 = function() {
   x$add("clust.cmeans", LearnerClustCMeans)
   x$add("clust.dbscan", LearnerClustDBSCAN)
   x$add("clust.xmeans", LearnerClustXMeans)
+  x$add("clust.cobweb", LearnerClustCobweb)
 
   x = utils::getFromNamespace("mlr_measures", ns = "mlr3")
   x$add("clust.db", MeasureClustInternal, name = "db")