MultiCons: MultiCons Consensus Clustering Algorithm
In doMIsaul: Do Multiple Imputation-Based Semi-Supervised and Unsupervised Learning

Description Usage Arguments Value Examples

Performs MultiCons clustering, from Al-Najdi et Al. For some reason, if you want to use mclust() clustering, the package needs to be loaded manually

MultiCons(
  DB,
  Clust_entry = FALSE,
  Clustering_selection = c("kmeans", "pam", "OPTICS", "agghc", "AGNES", "DIANA",
    "MCLUST", "CMeans", "FANNY", "BaggedClust"),
  num_algo = 10,
  maxClust = 10,
  sim.indice = "Jaccard",
  returnAll = FALSE,
  Plot = TRUE,
  verbose = FALSE
)

`DB`	Either data or dataframe of partitions.
`Clust_entry`	Is DB partitions (`TRUE`) or data (`FALSE`).
`Clustering_selection`	If DB is data, clustering algorithm to select among. Must be included in default value.
`num_algo`	Number of clustering algorithms to perform.
`maxClust`	Maximum number of clusters.
`sim.indice`	Index for defining best partition. Passed to `clusterCrit::extCriteria)()`, see `clusterCrit::getCriteriaNames(FALSE)` for other available indexes. If more than one index are given, only the first one will be used.
`returnAll`	Should all partitions (`TRUE`) or only the best (`FALSE`) be returned.
`Plot`	Should tree be plotted.
`verbose`	Passed on to `mclust()` and other functions.

A list of 2: performances and partitions. If returnAll is TRUE, both elements of the list contain results for all levels of the tree, else they only contain the results for the best level of the tree.

library(mclust)
### With clustering algorithm choices
MultiCons(iris[, 1:4],
          Clustering_selection = c("kmeans", "pam", "DIANA", "MCLUST"),
          Plot = TRUE)
### With a manual clustering entry
parts <- data.frame(factor(rep(c(1,2,3), each = 50)),
                    factor(rep(c(1,2,3), times = c(100, 25, 25))),
                    factor(rep(c(1,2), times = c(50, 100))),
                    factor(rep(c(3, 2, 1), times = c(120, 10, 20))),
                    stringsAsFactors = TRUE)
MultiCons(parts, Clust_entry = TRUE, Plot = TRUE)