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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
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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
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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
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Polikar, R. (2006). "Ensemble based systems in decision making".
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among its member partitions about what the optimal partition is.
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updating procedure. The final solution is found by achieving
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