PenalizedRegressionBasedClustering function

Penalized Regression-Based Clustering of [Wu et al., 2016].

Penalized Regression-Based Clustering of [Wu et al., 2016].

Clustering is performed through penalized regression with grouping pursuit

PenalizedRegressionBasedClustering(Data, FirstLambda, SecondLambda, Tau, PlotIt = FALSE, ...)

Arguments

  • 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.
  • FirstLambda: Set 1 for quadratic penalty based algorithm, 0.4 for revised ADMM.
  • SecondLambda: The magnitude of grouping penalty.
  • Tau: Tuning parameter: tau, related to grouping penalty.
  • PlotIt: Default: FALSE, if TRUE plots the first three dimensions of the dataset with colored three-dimensional data points defined by the clustering stored in Cls
  • ...: Further arguments for PRclust, enables also usage of [Pan et al., 2013].

Details

Parameters are rather challenging to choose.

Returns

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

References

[Pan et al., 2013] Pan, W., Shen, X., & Liu, B.: Cluster analysis: unsupervised learning via supervised learning with a non-convex penalty, The Journal of Machine Learning Research, Vol. 14(1), pp. 1865-1889. 2013.

[Wu et al., 2016] Wu, C., Kwon, S., Shen, X., & Pan, W.: A new algorithm and theory for penalized regression-based clustering, The Journal of Machine Learning Research, Vol. 17(1), pp. 6479-6503. 2016.

Author(s)

Michael Thrun

Note

Data matrix is internally transposed in order to fit the definition of the algorithm.

Examples

data(Hepta) Data=Hepta$Data out=PenalizedRegressionBasedClustering(Data,0.4,1,2,PlotIt=FALSE) table(out$Cls,Hepta$Cls)
  • Maintainer: Michael Thrun
  • License: GPL-3
  • Last published: 2023-10-19

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