mlr_learners_clust.ap: Affinity Propagation Clustering Learner

mlr_learners_clust.apR Documentation

Affinity Propagation Clustering Learner

Description

A LearnerClust for Affinity Propagation clustering implemented in apcluster::apcluster(). apcluster::apcluster() doesn't have set a default for similarity function. Therefore, the s parameter here is set to apcluster::negDistMat(r = 2L) by default since this is what is used in the original paper on Affity Propagation clustering. The predict method computes the closest cluster exemplar to find the cluster memberships for new data. The code is taken from StackOverflow answer by the apcluster package maintainer.

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("clust.ap")
lrn("clust.ap")

Meta Information

  • Task type: “clust”

  • Predict Types: “partition”

  • Feature Types: “logical”, “integer”, “numeric”

  • Required Packages: mlr3, mlr3cluster, apcluster

Parameters

Id Type Default Levels Range
s untyped apcluster::negDistMat, 2 -
p untyped NA -
q numeric - [0, 1]
maxits integer 1000 [1, \infty)
convits integer 100 [1, \infty)
lam numeric 0.9 [0.5, 1]
includeSim logical FALSE TRUE, FALSE -
details logical FALSE TRUE, FALSE -
nonoise logical FALSE TRUE, FALSE -
seed integer - (-\infty, \infty)

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustAP

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
LearnerClustAP$new()

Method clone()

The objects of this class are cloneable with this method.

Usage
LearnerClustAP$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

if (requireNamespace("apcluster")) {
  learner = mlr3::lrn("clust.ap")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}

mlr3cluster documentation built on March 31, 2023, 11:11 p.m.