Feature performance overview

Overview of Feature Values

The following measures were taken for the results of each feature:

obs (number of observations within the feature set)
NAs (number of NAs, i.e., missing values, within the feature set)
min (minimum), mean (arithmetic mean), max (maximum), std_dev (standard deviation)
1st_qu (1st quartile = lower quartile = 25%-quantile)
median (median = 50%-quantile)
3rd_qu (3rd quartile = upper quartile = 75%-quantile)
co_var (coefficient of variation = standard deviation / arithmetic mean)

Instance Feature Values

	obs	nas	min	qu_1st	med	mean	qu_3rd	max	sd	coeff_var
nvarsOrig	1614	20	20	3.8e+02	1.3e+03	5.1e+04	3e+04	2.3e+06	1.5e+05	2.9
nclausesOrig	1614	20	80	3.2e+03	2.2e+04	3.7e+05	1.9e+05	1.3e+07	1.3e+06	3.4
nvars	1614	20	3	3.5e+02	1.1e+03	2e+04	1.3e+04	7e+05	6e+04	3
nclauses	1614	20	12	2.9e+03	1.9e+04	2.8e+05	1.2e+05	1.3e+07	1.1e+06	4.1
reducedVars	1614	20	0	0	0.04	1.3	0.8	1.4e+02	5.9	4.7
reducedClauses	1614	20	0	0	0.011	0.44	0.36	85	2.7	6.1
vars_clauses_ratio	1614	20	0.0001	0.044	0.14	0.14	0.23	0.51	0.1	0.75
POSNEG_RATIO_CLAUSE_mean	1614	20	0.04	0.37	0.47	0.51	0.5	1	0.21	0.42
POSNEG_RATIO_CLAUSE_coeff_variation	1614	20	0	0.58	0.65	0.64	0.77	3.1	0.32	0.51
POSNEG_RATIO_CLAUSE_min	1614	20	0	0	0	0.14	0.14	1	0.3	2.1
POSNEG_RATIO_CLAUSE_max	1614	20	1	1	1	1	1	1	0	0
POSNEG_RATIO_CLAUSE_entropy	1614	20	0	0.71	1	1	1.4	3	0.58	0.56
VCG_CLAUSE_mean	1614	20	0	0.0002	0.0033	0.016	0.0096	0.67	0.038	2.4
VCG_CLAUSE_coeff_variation	1614	20	0	0.061	0.3	0.56	0.62	14	0.89	1.6
VCG_CLAUSE_min	1614	20	0	0.0002	0.0018	0.014	0.0077	0.67	0.037	2.6
VCG_CLAUSE_max	1614	20	0	0.0024	0.01	0.028	0.039	0.67	0.045	1.6
VCG_CLAUSE_entropy	1614	20	0	0.13	0.43	0.64	1.1	2.6	0.63	0.98
UNARY	1614	20	0	0	0	0	0	0	0
BINARYp	1614	20	0	0	0.083	0.26	0.52	1	0.34	1.3
TRINARYp	1614	20	0	0.21	0.82	0.63	0.96	1	0.38	0.6
VCG_VAR_mean	1614	20	0	0.0002	0.0033	0.016	0.0096	0.67	0.038	2.4
VCG_VAR_coeff_variation	1614	20	0	0.1	0.29	0.91	1.1	22	1.7	1.9
VCG_VAR_min	1614	20	0	0	0.0007	0.013	0.005	0.67	0.037	2.9
VCG_VAR_max	1614	20	0	0.0034	0.011	0.034	0.025	0.71	0.084	2.5
VCG_VAR_entropy	1614	20	0	2.4	2.7	2.8	3.6	6.6	1.3	0.49
POSNEG_RATIO_VAR_mean	1614	20	0	0.077	0.22	0.22	0.29	1	0.17	0.8
POSNEG_RATIO_VAR_stdev	1614	20	0	0.046	0.15	0.13	0.17	0.42	0.091	0.72
POSNEG_RATIO_VAR_min	1614	20	0	0	0	0.034	0	1	0.1	3
POSNEG_RATIO_VAR_max	1614	20	0	0.33	0.79	0.66	1	1	0.35	0.53
POSNEG_RATIO_VAR_entropy	1614	20	0	1.8	2.8	2.4	3.3	4.4	1.2	0.49
HORNY_VAR_mean	1614	20	0	0.0001	0.0011	0.0037	0.0039	0.5	0.016	4.2
HORNY_VAR_coeff_variation	1614	20	0	0.23	0.4	1	1.1	28	1.9	1.8
HORNY_VAR_min	1614	20	0	0	0.0001	0.0023	0.0014	0.5	0.016	6.8
HORNY_VAR_max	1614	20	0	0.0016	0.005	0.0087	0.0096	0.5	0.021	2.4
HORNY_VAR_entropy	1614	20	0	2.1	2.4	2.5	2.9	6.3	1.1	0.42
horn_clauses_fraction	1614	20	0.0071	0.35	0.5	0.52	0.71	1	0.27	0.52
VG_mean	1614	20	0	0.0004	0.0035	0.011	0.012	0.34	0.023	2.1
VG_coeff_variation	1614	20	0	0.076	0.29	0.65	0.89	12	0.93	1.4
VG_min	1614	20	0	0	0.0009	0.0088	0.0083	0.33	0.022	2.5
VG_max	1614	20	0	0.0032	0.0098	0.019	0.024	0.37	0.031	1.6
CG_mean	1614	809	0	0.0009	0.0084	0.025	0.018	0.58	0.047	1.9
CG_coeff_variation	1614	809	0	0.23	0.25	0.48	0.66	3.5	0.48	1
CG_min	1614	809	0	0.0001	0.0026	0.017	0.011	0.58	0.039	2.3
CG_max	1614	809	0	0.0054	0.021	0.05	0.056	0.66	0.074	1.5
CG_entropy	1614	809	0	2.8	3	2.8	3.7	5.4	1.3	0.45
cluster_coeff_mean	1614	809	0	0.11	0.13	0.17	0.21	0.64	0.11	0.61
cluster_coeff_coeff_variation	1614	809	0	0.23	0.25	0.31	0.36	1.5	0.22	0.73
cluster_coeff_min	1614	809	0	0.027	0.048	0.076	0.089	0.64	0.093	1.2
cluster_coeff_max	1614	809	0	0.25	0.34	0.39	0.56	0.98	0.2	0.52
cluster_coeff_entropy	1614	809	0	1.1	2.3	2.1	2.9	4	0.98	0.47
DIAMETER_mean	1614	20	0	3	4.8	8.6	7.2	4e+02	20	2.3
DIAMETER_coeff_variation	1614	20	0	0	0.035	0.051	0.087	0.74	0.057	1.1
DIAMETER_min	1614	20	0	3	4	7.7	6	4e+02	18	2.4
DIAMETER_max	1614	20	0	3	5	9.6	8	5e+02	23	2.4
DIAMETER_entropy	1614	20	0	0	0.26	0.45	0.69	4.5	0.58	1.3
cl_num_mean	1614	20	0	1.1e+02	1.2e+03	1.9e+03	3.9e+03	4.9e+03	1.8e+03	0.95
cl_num_coeff_variation	1614	20	0	0.015	0.15	0.25	0.37	3	0.33	1.3
cl_num_min	1614	20	0	34	5.2e+02	1.6e+03	3.8e+03	4.9e+03	1.8e+03	1.1
cl_num_max	1614	20	0	2.6e+02	2.2e+03	2.3e+03	4.1e+03	4.9e+03	1.8e+03	0.81
cl_num_q90	1614	20	0	1.8e+02	1.9e+03	2.2e+03	4.1e+03	4.9e+03	1.9e+03	0.86
cl_num_q10	1614	20	0	45	6e+02	1.6e+03	3.8e+03	4.9e+03	1.8e+03	1.1
cl_num_q75	1614	20	0	1.5e+02	1.5e+03	2e+03	4e+03	4.9e+03	1.8e+03	0.9
cl_num_q25	1614	20	0	62	7.8e+02	1.7e+03	3.9e+03	4.9e+03	1.8e+03	1
cl_num_q50	1614	20	0	91	1.1e+03	1.9e+03	3.9e+03	4.9e+03	1.8e+03	0.96
cl_size_mean	1614	20	0	16	26	32	43	4.6e+02	29	0.9
cl_size_coeff_variation	1614	20	0	0.027	0.086	0.15	0.2	2.3	0.21	1.4
cl_size_min	1614	20	0	9.9	23	25	33	3.8e+02	23	0.95
cl_size_max	1614	20	0	21	31	44	55	5.5e+02	47	1.1
cl_size_q90	1614	20	0	20	30	39	50	5.5e+02	39	1
cl_size_q10	1614	20	0	11	23	26	35	3.8e+02	24	0.92
cl_size_q75	1614	20	0	18	28	36	48	5.5e+02	35	0.98
cl_size_q25	1614	20	0	13	25	28	39	3.8e+02	25	0.89
cl_size_q50	1614	20	0	16	26	32	42	4.7e+02	28	0.9
SP_bias_mean	1614	20	0	0.18	0.41	0.45	0.68	0.99	0.28	0.61
SP_bias_coeff_variation	1614	20	0	0.23	0.57	0.54	0.68	8.4	0.48	0.88
SP_bias_min	1614	20	0	0	0.0001	0.11	0.003	0.94	0.26	2.3
SP_bias_max	1614	20	0	0.65	0.97	0.8	1	1	0.29	0.36
SP_bias_q90	1614	20	0	0.37	0.71	0.65	0.88	1	0.29	0.44
SP_bias_q10	1614	20	0	0.029	0.086	0.23	0.45	0.98	0.29	1.3
SP_bias_q75	1614	20	0	0.26	0.58	0.57	0.82	1	0.31	0.54
SP_bias_q25	1614	20	0	0.075	0.21	0.34	0.59	1	0.3	0.9
SP_bias_q50	1614	20	0	0.15	0.4	0.46	0.75	1	0.31	0.67
SP_unconstraint_mean	1614	20	0	0.0055	0.057	0.084	0.093	0.5	0.11	1.3
SP_unconstraint_coeff_variation	1614	20	0	0.43	0.67	1	1	19	1.5	1.4
SP_unconstraint_min	1614	20	0	0	0	0.024	0.0034	0.5	0.076	3.2
SP_unconstraint_max	1614	20	0	0.032	0.28	0.32	0.47	1	0.29	0.92
SP_unconstraint_q90	1614	20	0	0.0099	0.13	0.14	0.18	0.99	0.14	1
SP_unconstraint_q10	1614	20	0	0.0001	0.0023	0.036	0.028	0.5	0.081	2.2
SP_unconstraint_q75	1614	20	0	0.0044	0.066	0.11	0.12	0.94	0.13	1.2
SP_unconstraint_q25	1614	20	0	0.0009	0.018	0.056	0.047	0.5	0.11	2
SP_unconstraint_q50	1614	20	0	0.0023	0.038	0.077	0.079	0.5	0.12	1.5
saps_BestSolution_Mean	1614	20	0	12	39	2.7e+04	6.1e+02	2.3e+06	1.8e+05	6.6
saps_BestSolution_CoeffVariance	1614	20	0	0.2	0.29	1.7	0.84	61	5.5	3.2
saps_FirstLocalMinStep_Mean	1614	20	0	28	1.4e+02	1.2e+03	1e+03	1.8e+04	2.3e+03	2
saps_FirstLocalMinStep_CoeffVariance	1614	20	0	0.038	0.079	0.15	0.16	1.4	0.24	1.6
saps_FirstLocalMinStep_Median	1614	20	0	28	1.4e+02	1.3e+03	1.1e+03	1.8e+04	2.4e+03	2
saps_FirstLocalMinStep_Q10	1614	20	0	9	88	8.2e+02	4.4e+02	1.8e+04	2.1e+03	2.6
saps_FirstLocalMinStep_Q90	1614	20	0	27	1.4e+02	1.2e+03	8.4e+02	1.8e+04	2.4e+03	2.1
saps_BestAvgImprovement_Mean	1614	20	0	0.93	1.6	51	4.9	1.8e+04	6e+02	12
saps_BestAvgImprovement_CoeffVariance	1614	20	0	0.14	0.23	0.3	0.33	3.9	0.31	1
saps_FirstLocalMinRatio_Mean	1614	20	0	0.86	0.91	1.3	1	72	2.8	2.2
saps_FirstLocalMinRatio_CoeffVariance	1614	20	0	0.011	0.038	0.094	0.085	2.7	0.21	2.3
gsat_BestSolution_Mean	1614	20	0	12	36	1.5e+04	6.3e+02	1.7e+06	1.2e+05	8.2
gsat_BestSolution_CoeffVariance	1614	20	0	0.14	0.25	1.4	0.41	68	5.9	4.3
gsat_FirstLocalMinStep_Mean	1614	20	0	62	2.2e+02	3e+03	2.2e+03	6.8e+04	7.4e+03	2.5
gsat_FirstLocalMinStep_CoeffVariance	1614	20	0	0.03	0.077	0.13	0.15	1.4	0.2	1.5
gsat_FirstLocalMinStep_Median	1614	20	0	62	2.2e+02	3.1e+03	2.3e+03	6.8e+04	7.6e+03	2.4
gsat_FirstLocalMinStep_Q10	1614	20	0	19	1.2e+02	2.2e+03	8.8e+02	6.8e+04	7e+03	3.1
gsat_FirstLocalMinStep_Q90	1614	20	0	63	2.1e+02	3e+03	2.1e+03	6.8e+04	7.4e+03	2.5
gsat_BestAvgImprovement_Mean	1614	20	0	0.36	0.81	20	2.7	4.3e+03	1.8e+02	8.6
gsat_BestAvgImprovement_CoeffVariance	1614	20	0	0.26	0.39	0.53	0.52	4.2	0.5	0.96
gsat_FirstLocalMinRatio_Mean	1614	20	0	0.85	0.9	0.97	0.99	20	0.66	0.68
gsat_FirstLocalMinRatio_CoeffVariance	1614	20	0	0.0069	0.031	0.081	0.072	6.3	0.28	3.4
lobjois_mean_depth_over_vars	1614	20	0.0087	0.2	0.32	0.4	0.6	1	0.27	0.68
lobjois_log_num_nodes_over_vars	1614	20	0.026	0.47	0.62	0.61	0.82	1	0.26	0.42

Summary of feature steps

The following table summarizes the feature steps over all instances.

size (percentage of features affected by this step)
ok, ..., other (percentage of run status)
cost_min, cost_mean, cost_max (range of costs for this step)
cost_na (percentage of missing values occuring in costs)

	size	ok	presolved	crash	cost_min	cost_mean	cost_max	cost_na
Basic	2	99	1.2	0	0	0.048	2.4	0.011
CG	2	50	1.1	49	0	25	1.7e+04	0.011
DIAMETER	2	99	1.2	0	0	1.1	3.6	0.012
KLB	2	99	1.2	0	0	9.9	1.2e+03	0.011
Pre	1	99	1.2	0	0	5.6	1.6e+03	0.00062
cl	2	99	1.2	0	0	1.9	2	0.012
lobjois	2	99	1.2	0	0.01	2.3	5.1e+02	0.012
ls_gsat	2	99	1.2	0	0.03	2.4	13	0.012
ls_saps	2	99	1.2	0	0.18	2.2	14	0.012
sp	2	99	1.2	0	0	3	4.3e+02	0.012

Duplicated Features

Underneath, you'll find blocks of duplicated instnace features, i.e., observations that have equal values over all features. Please note, that only a maximum of 5 duplicates per block are shown.

block	numbers	instances
1	3	SAT_Competition2007/crafted/Medium/contest05/pebbling/sat-grid-pbl-0070.sat05-1334.reshuffled-07.cnf +++++++ SAT_Competition2007/crafted/Medium/contest05/pebbling/sat-grid-pbl-0200.sat05-1339.reshuffled-07.cnf +++++++ SAT_Competition2009/CRAFTED/Difficult/contest05/sabharwal/grid-pebbling-sat-grid-pbl-0300.sat05-1341.sat05-1341.reshuffled-07.cnf
2	17	SAT_Competition2007/industrial/industrial/babic/dspam/dspam_dump_vc1081.cnf +++++++ SAT_Competition2007/industrial/industrial/babic/dspam/dspam_dump_vc1093.cnf +++++++ SAT_Competition2007/industrial/industrial/babic/dspam/dspam_dump_vc1103.cnf +++++++ SAT_Competition2007/industrial/industrial/babic/dspam/dspam_dump_vc949.cnf +++++++ SAT_Competition2007/industrial/industrial/babic/hsatv17/hsat_vc11773.cnf +++++++ ...