View source: R/ModelBasedVarSelClustering.R
ModelBasedVarSelClustering | R Documentation |
Model-based clustering with variable selection and estimation of the number of clusters which is either based on [Marbac/Sedki, 2017],[Marbac et al., 2020], or on [Scrucca and Raftery, 2014].
ModelBasedVarSelClustering(Data,ClusterNo,Type,PlotIt=FALSE, ...)
Data |
[1:n,1:d] matrix of dataset to be clustered. It consists of n cases of d-dimensional data points. Every case has d attributes, variables or features. |
ClusterNo |
Numeric which defines number of cluster to search for. |
Type |
String, either |
PlotIt |
(optional) Boolean. Default = FALSE = No plotting performed. |
... |
Further arguments passed on to VarSelCluster or clustvarsel. |
List of
Cls |
[1:n] numerical vector with n numbers defining the classification as the main output of the clustering algorithm. It has k unique numbers representing the arbitrary labels of the clustering. |
Object |
Object defined by clustering algorithm as the other output of this algorithm |
Quirin Stier, Michael Thrun
[Marbac/Sedki, 2017] Marbac, M. and Sedki, M.: Variable selection for model-based clustering using the integrated complete-data likelihood. Statistics and Computing, 27(4), pp. 1049-1063, 2017.
[Marbac et al., 2020] Marbac, M., Sedki, M., & Patin, T.: Variable selection for mixed data clustering: application in human population genomics, Journal of Classification, Vol. 37(1), pp. 124-142. 2020.
# Hepta
data("Hepta")
Data = Hepta$Data
V = ModelBasedVarSelClustering(Data, ClusterNo=7,Type="VarSelLCM")
Cls = V$Cls
ClusterAccuracy(Hepta$Cls, Cls, K = 7)
V = ModelBasedVarSelClustering(Data, ClusterNo=7,Type="clustvarsel")
Cls = V$Cls
ClusterAccuracy(Hepta$Cls, Cls, K = 7)
## Not run:
# Hearts
heart=VarSelLCM::heart
ztrue <- heart[,"Class"]
Data <- heart[,-13]
V <- ModelBasedVarSelClustering(Data,2,Type="VarSelLCM")
Cls = V$Cls
ClusterAccuracy(ztrue, Cls, K = 2)
## End(Not run)
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