TESI DOCTORAL - La Salle
TESI DOCTORAL - La Salle
TESI DOCTORAL - La Salle
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3.2. Random hierarchical consensus architectures<br />
Consensus Diversity Dataset<br />
function scenario Zoo Iris Wine Glass Ionosphere WDBC Balance MFeat miniNG Segmentation BBC PenDigits<br />
|dfA| = 1 flat† flat† flat† flat† flat† flat† flat† flat† s=2,bm s=2,bm flat –<br />
|df<br />
CSPA A| = 10 s=2,bm† flat† s=2,bm s=3,bM s=2,bm† s=2,bm† flat† flat† s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 19 s=3,bm flat s=3,bM s=3,bM s=2,bm† s=3,bM flat† s=3,bM s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 28 s=2,bm† s=3,bM s=3,bm s=3,bM s=2,bm† s=3,bM flat s=3,bm s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 1 flat† flat† flat† flat† flat† flat† flat† flat† flat flat flat –<br />
|df<br />
EAC A| = 10 s=2,bm† flat† s=2,bm s=3,bM s=2,bm† s=2,bm† flat† flat† flat s=2,bm s=3,bM –<br />
|dfA| = 19 s=2,bm† s=3,bM s=3,bM s=3,bM s=2,bm† s=3,bM flat† flat† s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 28 s=2,bm† s=3,bM s=2,bm† s=3,bM s=2,bm† s=3,bM s=2,bm flat† s=2,bm s=2,bm s=2,bm –<br />
|dfA| = 1 flat† flat† flat† flat† s=3,bM s=3,bM flat† flat† s=3,bm s=3,bm s=2,bm s=3,bM<br />
|df<br />
HGPA A| = 10 s=3,bM flat† s=2,bm s=3,bM s=4,bM s=3,bm s=2,bm† s=3,bM s=6 s=4,bm s=2,bm s=4,bM<br />
|dfA| = 19 s=3,bm† s=3,bM s=3,bM s=4,bM s=2,bm† s=4,bM s=2,bm† s=4,bM s=2,bM s=4,bM s=6 s=3,bm<br />
|dfA| = 28 s=3,bm s=3,bM s=3,bm s=3,bM s=3,bm s=3,bm† s=3,bm s=3,bm† s=3,bM s=5,bm s=6 s=4,bM<br />
|dfA| = 1 s=2,bm† flat† flat† flat† s=3,bM s=3,bM flat† flat† s=3,bm s=2,bm s=2,bm s=3,bM<br />
|df<br />
MCLA A| = 10 s=3,bm† s=2,bm† s=2,bm s=3,bm s=4,bM s=2,bm† s=2,bm† s=3,bM s=5 s=4,bm s=4,bm s=4,bM<br />
|dfA| = 19 s=2,bm s=3,bM s=3,bM s=4,bM s=2,bm† s=4,bM s=2,bm† s=4,bM s=2,bM s=4,bM s=4,bm s=3,bm<br />
|dfA| = 28 s=3,bm† s=2,bm† s=3,bm s=3,bm† s=4,bM s=4,bm s=2,bm† s=3,bm† s=3,bM s=5,bm s=3,bM s=4,bM<br />
|dfA| = 1 flat† flat† flat† flat† flat† flat† flat† flat† flat flat flat –<br />
|df<br />
ALSAD A| = 10 s=3,bM flat† s=2,bm s=3,bM s=2,bm† s=2,bm† flat† flat† s=3,bM flat s=3,bM –<br />
|dfA| = 19 s=2,bm† s=3,bM s=3,bM s=2,bm† s=2,bm† s=3,bM flat† flat† s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 28 s=4,bM s=2,bm† s=3,bM s=3,bm s=2,bm† s=3,bM flat† flat† s=3,bm s=2,bm s=2,bm –<br />
|dfA| = 1 flat† flat† flat† flat† flat† flat† flat† flat† flat flat flat –<br />
|df<br />
KMSAD A| = 10 s=2,bm† flat† s=2,bm s=3,bM s=4,bM s=2,bm† flat† flat† s=3,bM s=3,bm s=2,bM –<br />
|dfA| = 19 s=2,bm† s=3,bM s=3,bM s=3,bm s=3,bm s=3,bM s=2,bm flat† s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 28 s=2,bm† s=2,bm† s=4,bM s=3,bM s=2,bm† s=3,bM s=4,bM flat† s=3,bM s=2,bm s=3,bm –<br />
|dfA| = 1 s=2,bM flat† flat† flat† flat† flat† flat† flat† flat flat flat –<br />
|df<br />
SLSAD A| = 10 s=3,bM flat† s=2,bm s=3,bM s=2,bm† s=2,bm† flat† flat† s=3,bM s=2,bm s=3,bM –<br />
|dfA| = 19 s=2,bm† s=2,bM s=3,bM s=4,bM s=2,bm† s=3,bM flat† flat† s=3,bM s=2,bm s=2,bm –<br />
|dfA| = 28 s=3,bm s=2,bm† s=3,bM s=3,bm s=2,bm† s=3,bM flat† flat† s=3,bm s=2,bm s=2,bm –<br />
68<br />
Table 3.5: Computationally optimal consensus architectures (flat or RHCA) on the unimodal data collections assuming a fully parallel<br />
implementation. The dagger (†) symbolizes optimal consensus architecture correct predictions.
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