Stupid k-centroids random clustering
Picks k random centroids from given dataset and assigns every point to closest centroid. This is called stupid k-centroids in Hennig (2019).
stupidkcentroids(xdata, k, distances = inherits(xdata, "dist"))
xdata |
cases*variables data, |
k |
integer. Number of clusters. |
distances |
logical. If |
The clustering vector (values 1 to k, length number of objects
behind xdata),
Hennig, C. (2019) Cluster validation by measurement of clustering characteristics relevant to the user. In C. H. Skiadas (ed.) Data Analysis and Applications 1: Clustering and Regression, Modeling-estimating, Forecasting and Data Mining, Volume 2, Wiley, New York 1-24, https://arxiv.org/abs/1703.09282
Akhanli, S. and Hennig, C. (2020) Calibrating and aggregating cluster validity indexes for context-adapted comparison of clusterings. Statistics and Computing, 30, 1523-1544, https://link.springer.com/article/10.1007/s11222-020-09958-2, https://arxiv.org/abs/2002.01822
set.seed(20000) options(digits=3) face <- rFace(200,dMoNo=2,dNoEy=0,p=2) stupidkcentroids(dist(face),3)
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