clusterHD (version 1.0.2)

diagPlot: diagnostic plots for HTK-Means Clustering

Description

Make diagnostic plots for HTK-means clustering.

Usage

diagPlot(HTKmeans.out, type = 1)

Value

No return value, makes the plot directly.

Arguments

HTKmeans.out

the output of a call to HTKmeans.

type

if type = 1, plots the regularization path. If type = 2, plots the differences in WCSS and ARI against the number of active variables.

Author

J. Raymaekers and R.H. Zamar

Details

This visualization plots the regularization path or the differences in WCSS and ARI against the number of active variables.

References

Raymaekers, Jakob, and Ruben H. Zamar. "Regularized K-means through hard-thresholding." arXiv preprint arXiv:2010.00950 (2020).

See Also

HTKmeans

Examples

X <- iris[, -5]
lambdas <- seq(0, 1, by = 0.01)
HTKmeans.out <- HTKmeans(X, 3, lambdas)
# \donttest{
diagPlot(HTKmeans.out, 1)
diagPlot(HTKmeans.out, 2)
# }