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Table 1 Properties of the generated dataset settings.

From: BiC2PAM: constraint-guided biclustering for biological data analysis with domain knowledge

Non-exhaustive list of matrices (\(\sharp\)rows \(\times\) \(\sharp\)columns) 500 × 50 1000 × 100 2000 × 200 4000 × 400
Number of hidden biclusters (K) \(6\times \frac{1}{\mu }\) \(10\times \frac{1}{\mu }\) \(15\times \frac{1}{\mu }\) \(20\times \frac{1}{\mu }\)
Number of rows per hidden bicluster \(\mu\)[50,70] \(\mu\)[70,100] \(\mu\)[100,200] \(\mu\)[200,300]
Number of columns per hidden bicluster \(\mu\)[5,7] \(\mu\)[7,10] \(\mu\)[8,12] \(\mu\)[10,15]
  1. where \(\mu\) defines the flexibility of the underlying coherency assumption (\(\mu\) = 1 for constant and \(\mu\) = 2 for order-preserving)
  2. Additional properties (default settings in bold):
  3. Coherency strength \(\delta\) = {5, 10, 15, 20, 25, 33 %} (or symbols \(|\mathcal {L}|\) = {20, 10, 7, 5, 4, 3})
  4. Deviations on data values in {0, \(\varvec{\delta }\)/2, \({\delta }\), 2\(\delta\)}, and degree of noisy and missing elements in {0, 2, 5, 10 %}
  5. Overlapping degree \(\theta\) = {0, 0.1, 0.2, 0.4} with plaid effects\(^2\) described by f = {sum, product, weighted} (cumulative function) \(\nu\) = {1, 0.7, 0.4} (cumulative effect), \(\epsilon\) = {0.1, 0.2} (noise), \(\kappa\) = {0.5, 0.3, 0.1 K} (average number of interacting biclusters) and \(\phi\) = {1, 0.8, 0.5} (distribution of overlapping areas between the \(\kappa\) bics)— variables according to [20]