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Given an initial large set of neural networks, our approach is aimed to select the subset formed by the most error-independent nets.
F 2 is the subset formed by all triangles T ∈ T h ∖ F 1 such that T ¯ ⊂ Q h ¯.
F 3 is the subset formed by all triangles T ∈ T h such that T ¯ ∩ Q h ¯ ≠ ∅ and T ⊄ Q h ¯.
It is possible to determine a number of association rules from each frequent itemset by splitting the set into two non-empty disjoint subsets of the given itemset such that one subset forms the antecedent of the rule and the other subset forms the consequent of the rule.
We define (R={1,ldots, m-1}subset mathfrak {M}) as the subset formed by the intermediate nodes (relays), and (T_{j}={s,1,ldots,j-1}subset mathfrak {M}) (for j=1,…,m) as the subset of nodes from which node j receives their transmitted symbols.
First, for each node in a one-hop distance from it is required to consider a new vertex subset formed by those vertices that simultaneously belong to the order 2 's neighbourhood and are direct neighbours of (see Figure 1(a)).
Kulkarny and Jackson described the formation of a related platelet subset forming on collagen surfaces under flow condition (SCIP, sustained calcium-induced platelet morphology) with procoagulant and pro-inflammatory properties [25].
This latter subset formed the actual study population.
Colored clades are statistically significant except for the scale β-keratins, which only have a subset forming a significant clade.
The remaining subset forms the test set (TS) in which predictions derived from the ES are tested for their validity by correlating predicted and observed data.
Four of these subsets were combined to form the estimation set (ES) and the remaining subset formed the test set (TS) in which predictions derived from ES were tested for their validity by correlating predicted and observed data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com