IntClust (version 0.1.0)

HierarchicalEnsembleClustering: Hierarchical ensemble clustering

Description

Zheng2014IntClust proposed the Hierarchical Ensemble Clustering (HEC) algorithm. For each dendrogram, the cophenetic distances between the object are calculated. The distances are aggregated across the data sets and an ultra-metric which is the closest to the distance matrix is determined. A final hierarchical clustering is based on the ultra-metric values.

Usage

HierarchicalEnsembleClustering(List, type = c("data", "dist", "clust"),
  distmeasure = c("tanimoto", "tanimoto"), normalize = c(FALSE, FALSE),
  method = c(NULL, NULL), clust = "agnes", linkage = c("flexible",
  "flexible"), alpha = 0.625)

Arguments

List

A list of data matrices. It is assumed the rows are corresponding with the objects.

type

indicates whether the provided matrices in "List" are either data matrices, distance matrices or clustering results obtained from the data. If type="dist" the calculation of the distance matrices is skipped and if type="clusters" the single source clustering is skipped. Type should be one of "data", "dist" or"clusters".

distmeasure

A vector of the distance measures to be used on each data matrix. Should be one of "tanimoto", "euclidean", "jaccard", "hamming". Defaults to c("tanimoto","tanimoto").

normalize

Logical. Indicates whether to normalize the distance matrices or not, default is FALSE. This is recommended if different distance types are used. More details on normalization in Normalization

method

A method of normalization. Should be one of "Quantile","Fisher-Yates", "standardize","Range" or any of the first letters of these names. Default is c(NULL,NULL) for two data sets.

clust

Choice of clustering function (character). Defaults to "agnes".

linkage

Choice of inter group dissimilarity (character) for each data set. Defaults to c("flexible", "flexible") for two data sets.

alpha

The parameter alpha to be used in the "flexible" linkage of the agnes function. Defaults to 0.625 and is only used if the linkage is set to "flexible".

Value

The returned value is a list of two elements:

DistM

The resulting distance matrix

Clust

The resulting hierarchical structure

The value has class 'HEC'.

References

Zheng2014IntClust

Examples

# NOT RUN {
data(fingerprintMat)
data(targetMat)
L=list(fingerprintMat,targetMat)

MCF7_HEC=HierarchicalEnsembleClustering(List=L,type="data",distmeasure=
c("tanimoto","tanimoto"),normalize=c(FALSE,FALSE),method=c(NULL,NULL),
clust="agnes",linkage=c("flexible","flexible"),alpha=0.625)
# }