A random partition of all proteins is generated by shuffing the input PPIs in the following way.
Restricted Neighborhood Search Clustering (RNSC) algorithm [ 9] is another kind of clustering algorithm based on graph partitioning, which starts with a random partition of a network and iteratively moves the nodes on the border of a cluster into the adjacent cluster to search for a better clustering result with the minimum cost.
For this, the excess of internal edges relative to the number of edges expected for a random partition into classes having the same number of elements, is often quantified using the modularity criterion defined by Newman for strict partitions (Newman, 2004).
If the values of BW r, s for the proposed three clusters are significantly higher than for a random partition we take this as evidence that the clusters found indeed constitute meaningful groups also at the level of individual subjects.
RPMF [28] adopted a random partition approach to group similar users and items by taking advantage of decision trees.
Since the results of cross-validation usually depend highly on the chosen random partition of the data [ 42, 43], we repeat cross-validation 100 times for different random partitions and finally average the results over these repetitions.
To demonstrate superiority of FastHap partitioning algorithm over a random partitioning, we selected a subset of the dataset at random.
For this purpose, we have selected stochastic tessellations of the Poisson, Voronoi and Box type, which provide convenient models for the random partitioning of space, and we have generated an ensemble of assembly realizations; for each geometry realization, criticality calculations have been performed by using the Monte Carlo code Tripoli-4®, developed at CEA.
These experiments have been repeated for 100 random partitions of the entire dataset.
We repeated this experiment for 250 random partitions of each breast cancer dataset, and estimated the distribution of the absolute error difference.
