The resulted partition can be nonmatched across adjacent subdomain interfaces.
The resulting partitioning problem is usually easy to solve with this algorithm.
However, the resulting partitioning cannot be built independently by the devices, since this approach considers only the matrix view of the circuit.
However, while closely examining the resulting partitioning in our visualization we noticed a common case where some code was rarely ever pushed to the public cloud, making automated partitioning less effective.
The optimized modularity is only slightly higher with Q = 0.557 and the resulting partitioning is very similar to the metabolite classes (see Additional file 3).
One such example is the utilization of various cluster validity indices, which incorporate statistical aspects of the resulting partitioning to provide a quantitative assessment of the quality of clustering results.
In Table 3 we show the level of similarity between the resulting partitions and the arXiv classification ones.
The process stops when all blocks are stable and the resulting partition is a stochastic bisimulation [6].
Modularity is a well-known metric that compares the number of connections inside a partition and between different resulting partitions of a network.
If the resulting partition improves the previous Q value, the merge is accepted and the algorithm advances towards further attempted mergers.
