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Secondly, a merging algorithm is developed based on initial segmenting and a rough partitioning of the network is obtained.
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(The rough partition of constrained rule set).
Section 3 presents a rough partition and then a stricter partition of the solution set.
From the partition in Proposition 1, we immediately obtain the following rough partition for ({mathcal F}{mathcal S}_{C_{10} subseteq C_{11},nsubseteq C_{21}}(s_0,s_0)).
In next section, we first present an ineffective rough partition of the solution set, and then, based on above approach, we show a better strict partition for it.
(Illustrating the disadvantage of the above rough partition) The rest of this paper considers dataset ({mathcal T}) shown in Fig. 1a.
Based on this rough partition (obtained from the lattice ({mathcal F}{mathcal L}{mathcal C}{mathcal G}) of frequent closed itemsets), association rules with constraints can be discovered in two steps.
In the case of Transylvania the rough partition in two reveals first the Banat region which is historically known to be different from the rest of Transylvania.
One can note the rough partition showing a division from east to west following the latitudes, and the finer partitions in 48 units (Alaska and Hawaii being not the subject of the analysis), revealing federal state-like structures.
We chose the 21-day cutoff as a rough-and-ready, approximate partition of mulitfactorial disease burden.
This method divides the cumulative probability into K partitions to form K frequency binnings which correspond to K clusters, a very rough word partition which only considers frequency.
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