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The algorithm looks for combinations of sets of mutations (bi-cliques) that are shared by five or more individuals in the data, using a recursive algorithm which combines the sets onto bigger sets until all maximal sets are identified.
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However, maximal ADT sets are not necessarily connected.
Some results about the existence of maximal m-open sets are given.
In case of SIM, the set C is maximal, whereas with MIMs both P and C sets are maximal.
An ST-set S is maximal if there is no ST-set T with S ⊊ T. Informally, the maximal ST-sets are the result of repeatedly collapsing pairs of unseparated taxa for as long as possible.
Most SL sets are not maximal cliques, but some SL sets are quite close to being maximal cliques.
Results for the individual classifiers using the minimal and maximal feature set are summarized in Table 2.
There are maximal sets of propositions that are not possible worlds because they are not consistent in the relevant sense.
A similar result for locally maximal chain transitive sets was proved in [3].
Very recently, Lee and Wen [5] showed that C1 generically, a locally maximal chain transitive sets is shadowable if and only if it is hyperbolic.
Lemma 2.12 [11, Theorem 4.10] For C1-generic f, a locally maximal transitive set is a locally maximal homoclinic class H V (p), where V is a compact neighborhood of H f (p), and H V (p) is a locally maximal in V. Corollary 2.13 For C1-generic f, a locally maximal transitive set is hyperbolic.
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CEO of Professional Science Editing for Scientists @ prosciediting.com