10
folds and 1
repetitions.The performance is measured in three different ways.
algo | model | succ | par10 | mcp |
---|---|---|---|---|
baseline | vbs | 0.853 | 3127.236 | 0.000 |
baseline | singleBest | 0.769 | 4893.141 | 190.904 |
baseline | singleBestByPar | 0.769 | 4893.141 | 190.904 |
baseline | singleBestBySuccesses | 0.769 | 4893.141 | 190.904 |
classif | rpart | 0.821 | 3795.520 | 64.070 |
classif | randomForest | 0.823 | 3743.180 | 54.879 |
classif | ksvm | 0.818 | 3836.658 | 62.058 |
cluster | XMeans | 0.820 | 3833.897 | 80.871 |
regr | lm | 0.822 | 3777.872 | 68.000 |
regr | rpart | 0.822 | 3789.716 | 79.841 |
regr | randomForest | 0.844 | 3321.285 | 21.339 |
The following default feature steps were used for model building:
group_basics
Number of presolved instances: 0
The cost for using the feature steps (adapted for presolving) is: 0
or on average: 0
The feature steps correspond to the following 37
/ 37
instance features:
numVars, numClauses, perc_soft, soft_mean, soft_std,
soft_min, soft_max, var_clauses_ratio, vcg_var_mean, vcg_var_std,
vcg_var_min, vcg_var_max, vcg_var_spread, vcg_cls_mean, vcg_cls_std,
vcg_cls_min, vcg_cls_max, vcg_cls_spread, pnr_var_mean, pnr_var_std,
pnr_var_min, pnr_var_max, pnr_var_spread, pnr_cls_mean, pnr_cls_std,
pnr_cls_min, pnr_cls_max, pnr_cls_spread, unary, binary,
trinary, horn_mean, horn_std, horn_min, horn_max,
horn_spread, horn
6
to 3
, resulting in a PAR10 score of 3322.795
for the reduced model. Analogously, the model that was generated based on 7
of the originally 30
features resulted in a PAR10 score of 3270.075
.
Below, you can find the list of the selected features and solvers:
Selected Features:
vcg_var_mean, vcg_var_min, vcg_cls_max, pnr_var_spread, pnr_cls_std,
unary, horn_max
Selected Solvers:
DSWPM1_924, akmaxsat, qmaxsat0.21g2comp