Extremal Ensemble Learning (EEL) is a

machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...

algorithmic paradigm for

graph partitioning In mathematics, a graph partition is the reduction of a Graph (discrete mathematics), graph to a smaller graph by partition of a set, partitioning its set of nodes into mutually exclusive groups. Edges of the original graph that cross between the g ...

. EEL creates an

ensemble Ensemble may refer to: Art * Architectural ensemble * Ensemble (album), ''Ensemble'' (album), Kendji Girac 2015 album * Ensemble (band), a project of Olivier Alary * Ensemble cast (drama, comedy) * Ensemble (musical theatre), also known as the ...

of partitions and then uses information contained in the ensemble to find new and improved partitions. The ensemble evolves and learns how to form improved partitions through extremal updating procedure. The final solution is found by achieving consensus among its member partitions about what the optimal partition is.

Reduced Network Extremal Ensemble Learning (RenEEL)

A particular implementation of the EEL paradigm is the Reduced Network Extremal Ensemble Learning (RenEEL) scheme for partitioning a graph. RenEEL uses consensus across many partitions in an ensemble to create a reduced network that can be efficiently analyzed to find more accurate partitions. These better quality partitions are subsequently used to update the ensemble. An algorithm that utilizes the RenEEL scheme is currently the best algorithm for finding the graph partition with maximum modularity, which is an NP-hard problem.

References

Machine learning algorithms Graph algorithms {{Compu-ai-stub