TESI DOCTORAL - La Salle

SERT RHCA (sec.)
PERT RHCA (sec.)
10 1
10 0
10 1
10 0
10 −1
s : number of stages
9 6 5 4 4 3 3 2 2 1
2 3 4 5 7 8 19 20 285 570
b : mini−ensemble size
(a) Serial estimated running time
s : number of stages
9 6 5 4 4 3 3 2 2 1
2 3 4 5 7 8 19 20 285 570
b : mini−ensemble size
(c) Parallel estimated running time
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
Chapter 3. Hierarchical consensus architectures
SRT RHCA (sec.)
PRT RHCA (sec.)
10 1
10 0
10 1
10 0
10 −1
s : number of stages
9 6 5 4 4 3 3 2 2 1
2 3 4 5 7 8 19 20 285 570
b : mini−ensemble size
(b) Serial real running time
s : number of stages
9 6 5 4 4 3 3 2 2 1
2 3 4 5 7 8 19 20 285 570
b : mini−ensemble size
(d) Parallel real running time
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
Figure 3.5: Estimated and real running times of the serial RHCA on the Zoo data collection
in the diversity scenario corresponding to a cluster ensemble of size l = 570.
of PRTRHCA —in fact, the only prediction error occurs in the case the SLSAD consensus
function is employed. In this case, according to PERTRHCA (figure 3.4(c)), the most efficient
consensus architecture is the RHCA variant with s = 2 stages using mini-ensembles of
size b = 28. However, the real execution times (figure 3.4(d)) reveal that flat consensus is
the fastest option when this consensus function is employed for combining the clusterings.
Nevertheless, we would like to highlight that the cost (measured in terms of running
time) of selecting this computationally suboptimal RHCA variant based on the PERTRHCA
prediction is almost negligible in absolute terms, as the difference between the running
times of the truly and allegedly optimal parallel RHCA variants is smaller than a tenth of
a second in this case.
Diversity scenario |df A| =10
Figure 3.5 presents the estimated and real execution times of several architectural variants of
both the fully serial and parallel RHCA implementations in the second diversity scenario,
the one resulting from employing |dfA| = 10 randomly chosen clustering algorithms for
generating a cluster ensemble of size l = 570. In this case, the sweep of values of the
mini-ensembles size is b = {2, 3, 4, 5, 7, 8, 19, 20, 285, 570}.
If the estimated and real execution times of the serial implementation of the RHCA are
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