| HierarchicalEnsembleClustering | R Documentation |
Zheng2014MosaiClusteR 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.
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
)
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 |
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". |
The returned value is a list of two elements:
DistM |
The resulting distance matrix |
Clust |
The resulting hierarchical structure |
The value has class 'HEC'.
Zheng2014MosaiClusteR
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