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Table 1 Comparison of the clustering results for the Golub dataset

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

Algorithm AEC AVI ACC (%)
Diffractive clustering 87.5 73.5 94.4
k‐means 76.1 62.6 88.9
Fuzzy c‐means 76.1 57.3 88.9
Hierarchical clustering (single) 59.3 63.7 63.9
Hierarchical clustering (centroid) 53.4 99.7 61.1
Self‐organising map 60.5 12.6 65.3
Gaussian Mixture Model 76.1 60.6 88.9
DBSCAN 53.1 75.7 68.1
  1. The clustering algorithms perform well as the two classes in the dataset are clearly separated, however the diffractive clustering algorithm outperforms the other algorithms in terms of accuracy.