Overview of performance values

The following statistics were calculated from the performance values of each algorithm:
obs nas min qu_1st med mean qu_3rd max sd coeff_var
X2clsQ 1368 0 0 26.0175 3600 2321.16 3600 3600 1647.05 0.70958
QuBE 1368 0 0.02 2.3175 3600 1930.78 3600 3600 1751.88 0.907344
quantor 1368 0 0 130.755 3600 2603.32 3600 3600 1595.67 0.612938
sKizzo 1368 0 0 0.8375 293.195 1617.01 3600 3600 1734.22 1.07248
sSolve 1368 0 0.72 1.5975 2082.43 1847.8 3600 3600 1747.01 0.945458

Summary of the runstatus per algorithm

The following table summarizes the runstatus of each algorithm over all instances (in %).

ok timeout memout not_applicable crash other
quantor 28.289 4.751 66.959 0.000 0.000 0.000
QuBE 49.050 43.640 7.310 0.000 0.000 0.000
sKizzo 57.675 0.000 42.325 0.000 0.000 0.000
sSolve 51.681 48.319 0.000 0.000 0.000 0.000
X2clsQ 39.620 51.243 9.137 0.000 0.000 0.000

Dominated Algorithms

Here, you'll find an overview of dominating/dominated algorithms:
None of the algorithms was superior to any of the other.

An algorithm (A) is considered to be superior to an other algorithm (B), if it has at least an equal performance on all instances (compared to B) and if it is better on at least one of them. A missing value is automatically a worse performance. However, instances which could not be solved by either one of the algorithms, were not considered for the dominance relation.


Visualisations

Important note w.r.t. some of the following plots:
If appropriate, we imputed performance values for failed or censored runs. We used max + 0.3 * (max - min), in case of minimization problems, or min - 0.3 * (max - min), in case of maximization problems.
In addition, a small noise is added to the imputed values (except for the cluster matrix, based on correlations, which is shown at the end of this page).

Boxplots of performance values


Imputing the performance values of failed or censored runs (as described in the red note at the beginning of this section):
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Discarding the performance values of failed or censored runs:
## Warning: Removed 3744 rows containing non-finite values (stat_boxplot).
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Estimated densitities of performance values


Imputing the performance values of failed or censored runs (as described in the red note at the beginning of this section):
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Discarding the performance values of failed or censored runs:
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Estimated cumulative distribution functions of performance values


Imputing the performance values of failed runs (as described in the red note at the beginning of this section):
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Discarding the performance values of failed or censored runs:
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Scatterplot matrix of the performance values

The figure underneath shows pairwise scatterplots of the performance values.

Imputing the performance values of failed and censored runs (as described in the red note at the beginning of this section):
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Clustering algorithms based on their correlations

The following figure shows the correlations of the ranks of the performance values. Per default it will show the correlation coefficient of spearman. Missing values were imputed prior to computing the correlation coefficients. The algorithms are ordered in a way that similar (highly correlated) algorithms are close to each other. Per default the clustering is based on hierarchical clustering, using Ward's method.

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