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Fig. 3 | BMC Bioinformatics

Fig. 3

From: Shrinkage Clustering: a fast and size-constrained clustering algorithm for biomedical applications

Fig. 3

Robustness of Shrinkage Clustering against noise. a The distribution density of SN is shown with a varying degree of noise, as ε is sampled with σ from 0 to 0.5. b The probability of successfully recovering the underlying cluster structure is plotted against different noise levels. The true cluster recovery is defined as the frequency of generating the exact same cluster assignment as the true cluster assignement when clustering the data with noise generated 1000 times

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