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Table 2 Comparison of the clustering results for the MILEs dataset

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

Algorithm AEC AVI ACC (%)
Diffractive clustering 66.6 179.0 73.1
k‐means 59.1 152.6 61.6
Fuzzy c‐means 62.9 171.4 71.4
Hierarchical clustering (single) 47.7 64.2 47.1
Hierarchical clustering (centroid) 56.4 155.2 60.9
Self‐organising map 46.1 10.6 47.1
Gaussian Mixture Model 58.6 96.4 61.2
DBSCAN 52.2 122.3 57.6
  1. The diffractive clustering algorithm outperforms the other clustering algorithms in terms of accuracy, with the hierarchical clustering algorithm performing better when there is centroid linkage.