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Table 1 Random data models for evaluation of the fuzzy clustering algorithm

From: Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

model

k

m

α

β

γ

description

1

2

(3, 3)

1

0.7

0.2

equal-sized, no overlap

2

2

(3, 4)

1

0.7

0.2

no cluster overlap

3

3

(3, 4, 5)

1.2

0.6

0.1

3-partite, low-noise

4

3

(3, 4, 5)

1.2

0.8

0.2

3-partite, noisy

  1. Parameters for the simulated data models. k denotes the number of partitions of the network, m is a vector with the number of clusters in each partition, α the backbone connectivity, β the cluster and γ the noise connectivity.