Scheme of optimal ensembles of clustering algorithms with a combined use of the Greedy Heuristics Method and a matched binary partitioning matrix

We propose a procedure for building optimal ensembles of automatic grouping (clustering) algorithms with a combined use of the genetic algorithm of the Greedy Heuristics Method and a matched binary partitioning matrix for practical problems. It is shown that our procedure allows us to increase the accuracy of separation of a mixed batch of industrial products into homogeneous batches.