Stochastic Block Models Family
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A Stochastic Block Models Family is a Random Graph Model that generalizes a Block Model Family to be Stochastic Model.
- Context:
- It can make use of a Stochastic Equivalence Measure (a measure of the degree to which sets of actors approach a definition in a given set of network data)
- See: Mixed Membership Stochastic Blockmodels.
References
2021
- (Wikipedia, 2021) ⇒ https://en.wikipedia.org/wiki/Stochastic_block_model Retrieved:2021-8-14.
- The stochastic block model is a generative model for random graphs. This model tends to produce graphs containing communities, subsets characterized by being connected with one another with particular edge densities. For example, edges may be more common within communities than between communities. Its mathematical formulation has been firstly introduced in 1983 in the field of social network by Holland et al. The stochastic block model is important in statistics, machine learning, and network science, where it serves as a useful benchmark for the task of recovering community structure in graph data.