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Table 4 Comparison of the clustering results for the Shipp dataset

From: Clustering gene expression data using a diffraction‐inspired framework

Algorithm AEC AVI ACC (%)
Diffractive clustering 55.5 160.6 63.6
k‐means 48.0 79.7 51.9
Fuzzy c‐means 48.7 82.0 51.9
Hierarchical clustering (single) 51.1 112.2 53.3
Hierarchical clustering (centroid) 51.1 113.6 53.2
Self‐organising map 47.7 14.7 53.3
Gaussian Mixture Model 49.8 66.8 51.9
DBSCAN 49.9 65.4 54.5
  1. The diffractive clustering algorithm outperforms the others in terms of accuracy, however all the algorithms perform relatively poorly due to the mixing between the two different classes.