3 citations · 9 across the 6 of their papers we have counts for
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An empirical comparison and characterisation of nine popular clustering methods
Christian Hennig
Nine popular clustering methods are applied to 42 real data sets. The aim is to give a detailed characterisation of the methods by means of several cluster validation indexes that…
An adequacy approach for deciding the number of clusters for OTRIMLE robust Gaussian mixture based clustering
Christian Hennig, Pietro Coretto
We introduce a new approach to deciding the number of clusters. The approach is applied to Optimally Tuned Robust Improper Maximum Likelihood Estimation (OTRIMLE; Coretto and Henni…
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes
Serhat Emre Akhanli, Christian Hennig
A key issue in cluster analysis is the choice of an appropriate clustering method and the determination of the best number of clusters. Different clusterings are optimal on the sam…
Minkowski distances and standardisation for clustering and classification of high dimensional data
Christian Hennig
There are many distance-based methods for classification and clustering, and for data with a high number of dimensions and a lower number of observations, processing distances is c…
Initialization methods for optimum average silhouette width clustering
Fatima Batool
A unified clustering approach that can estimate number of clusters and produce clustering against this number simultaneously is proposed. Average silhouette width (ASW) is a widely…
Quantile-based clustering
Christian Hennig, Cinzia Viroli, Laura Anderlucci
A new cluster analysis method, -quantiles clustering, is introduced. -quantiles clustering can be computed by a simple greedy algorithm in the style of the classical Lloyd's…