| obs | nas | min | qu_1st | med | mean | qu_3rd | max | sd | coeff_var |
X2361_weka.OneR | 105 | 0 | 0.036898 | 0.414 | 0.704942 | 0.647421 | 0.899552 | 1 | 0.274286 | 0.423659 |
X2362_weka.J48 | 105 | 0 | 0.188206 | 0.760131 | 0.871396 | 0.819622 | 0.953968 | 1 | 0.190278 | 0.232153 |
X2364_weka.IBk | 105 | 0 | 0.138 | 0.7322 | 0.88838 | 0.793618 | 0.963 | 1 | 0.233432 | 0.294137 |
X2367_weka.REPTree | 105 | 0 | 0.138889 | 0.730469 | 0.855072 | 0.802228 | 0.952601 | 1 | 0.201269 | 0.250887 |
X2368_weka.RandomTree | 105 | 0 | 0.126667 | 0.6745 | 0.832844 | 0.762269 | 0.916505 | 0.999825 | 0.20923 | 0.274484 |
X2369_weka.RandomForest | 105 | 0 | 0.195734 | 0.796321 | 0.930219 | 0.853415 | 0.97351 | 1 | 0.177608 | 0.208114 |
X2370_weka.LMT | 105 | 0 | 0.212045 | 0.818 | 0.91009 | 0.855673 | 0.971638 | 1 | 0.176554 | 0.206333 |
X2371_weka.HoeffdingTree | 105 | 0 | 0.00625 | 0.713551 | 0.845424 | 0.777035 | 0.936859 | 1 | 0.213784 | 0.275127 |
X2373_weka.JRip | 105 | 0 | 0.183864 | 0.746094 | 0.86095 | 0.813124 | 0.948801 | 1 | 0.190539 | 0.23433 |
X2381_weka.NaiveBayes | 105 | 0 | 0.173913 | 0.689655 | 0.8008 | 0.760041 | 0.908738 | 1 | 0.198041 | 0.260567 |
X2647_weka.Logistic | 105 | 0 | 0.166 | 0.749 | 0.859547 | 0.81341 | 0.946325 | 1 | 0.186974 | 0.229865 |
X2869_weka.SMO_PolyKernel | 105 | 0 | 0.2 | 0.758717 | 0.867483 | 0.82192 | 0.965049 | 1 | 0.194051 | 0.236095 |
X2882_weka.SMO_RBFKernel | 105 | 0 | 0.106942 | 0.663507 | 0.844907 | 0.759159 | 0.947269 | 1 | 0.241338 | 0.317903 |
X2889_weka.IBk | 105 | 0 | 0.18 | 0.737 | 0.882985 | 0.797888 | 0.9543 | 1 | 0.226108 | 0.283383 |
X2891_weka.HyperPipes | 105 | 0 | 0.045008 | 0.446377 | 0.683461 | 0.63796 | 0.877915 | 0.998449 | 0.266015 | 0.416978 |
X2893_weka.OLM | 105 | 0 | 0.009381 | 0.128155 | 0.4054 | 0.423398 | 0.658662 | 0.953704 | 0.287687 | 0.679473 |
X2894_weka.FURIA | 105 | 0 | 0.195734 | 0.787 | 0.893002 | 0.832574 | 0.965201 | 1 | 0.18972 | 0.227872 |
X2897_weka.ConjunctiveRule | 105 | 0 | 0.018136 | 0.298999 | 0.700231 | 0.598107 | 0.855072 | 0.97667 | 0.294418 | 0.49225 |
X2898_weka.SimpleCart | 105 | 0 | 0.138889 | 0.757941 | 0.87225 | 0.818857 | 0.957033 | 1 | 0.193076 | 0.235787 |
X2900_weka.LADTree | 105 | 0 | 0.186951 | 0.68236 | 0.831415 | 0.783457 | 0.948589 | 1 | 0.198358 | 0.253183 |
X2903_weka.AdaBoostM1_DecisionStump | 105 | 0 | 0.011875 | 0.300787 | 0.736 | 0.620457 | 0.899804 | 0.992 | 0.309975 | 0.499591 |
X2904_weka.AdaBoostM1_J48 | 105 | 0 | 0.188206 | 0.772727 | 0.9145 | 0.845988 | 0.971886 | 1 | 0.184606 | 0.218214 |
X2906_weka.Bagging_REPTree | 105 | 0 | 0.138889 | 0.789123 | 0.893468 | 0.828509 | 0.959656 | 1 | 0.192743 | 0.232639 |
X6250_weka.DecisionTable | 105 | 0 | 0.200753 | 0.65625 | 0.833884 | 0.769882 | 0.932067 | 1 | 0.206808 | 0.268624 |
X6352_weka.BayesNet | 105 | 0 | 0.204517 | 0.711695 | 0.840936 | 0.79034 | 0.930963 | 1 | 0.184037 | 0.232858 |
X6355_weka.AdaBoostM1_NaiveBayes | 105 | 0 | 0.173913 | 0.725 | 0.818051 | 0.780119 | 0.938494 | 1 | 0.203233 | 0.260516 |
X6378_weka.LogitBoost_DecisionStump | 105 | 0 | 0.212045 | 0.746403 | 0.870389 | 0.820406 | 0.953968 | 1 | 0.184494 | 0.224882 |
X8990_weka.MultilayerPerceptron | 105 | 0 | 0.006254 | 0.71875 | 0.860018 | 0.7674 | 0.9504 | 1 | 0.255597 | 0.333068 |
X8994_weka.MultilayerPerceptron | 105 | 0 | 0.00625 | 0.674107 | 0.851036 | 0.756521 | 0.950162 | 1 | 0.265377 | 0.350786 |
X8995_weka.MultilayerPerceptron | 105 | 0 | 0.143791 | 0.708 | 0.860018 | 0.78491 | 0.9625 | 1 | 0.23659 | 0.301423 |
| ok | timeout | memout | not_applicable | crash | other |
X2361_weka.OneR | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2362_weka.J48 | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2364_weka.IBk | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2367_weka.REPTree | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2368_weka.RandomTree | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2369_weka.RandomForest | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2370_weka.LMT | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2371_weka.HoeffdingTree | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2373_weka.JRip | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2381_weka.NaiveBayes | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2647_weka.Logistic | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2869_weka.SMO_PolyKernel | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2882_weka.SMO_RBFKernel | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2889_weka.IBk | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2891_weka.HyperPipes | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2893_weka.OLM | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2894_weka.FURIA | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2897_weka.ConjunctiveRule | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2898_weka.SimpleCart | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2900_weka.LADTree | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2903_weka.AdaBoostM1_DecisionStump | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2904_weka.AdaBoostM1_J48 | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X2906_weka.Bagging_REPTree | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X6250_weka.DecisionTable | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X6352_weka.BayesNet | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X6355_weka.AdaBoostM1_NaiveBayes | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X6378_weka.LogitBoost_DecisionStump | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X8990_weka.MultilayerPerceptron | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X8994_weka.MultilayerPerceptron | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
X8995_weka.MultilayerPerceptron | 100.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
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.