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	300	10	1.7e+02	1.4e+04	7.2e+04	1.6e+05	2e+05	2e+06	2.6e+05	1.6
nclausesOrig	300	10	1e+03	1.3e+05	3.6e+05	1.4e+06	1.1e+06	1.3e+07	2.6e+06	1.9
nvars	300	10	95	8.6e+03	2.7e+04	8.3e+04	8.1e+04	1.1e+06	1.5e+05	1.8
nclauses	300	10	6.6e+02	8e+04	2e+05	1.1e+06	7e+05	1.3e+07	2.2e+06	2.1
reducedVars	300	10	0	0.25	0.98	7.8	1.8	1.7e+03	1e+02	13
reducedClauses	300	10	0	0.045	0.45	2.2	0.79	4.5e+02	26	12
vars_clauses_ratio	300	10	0.0056	0.072	0.15	0.14	0.19	0.29	0.07	0.52
POSNEG_RATIO_CLAUSE_mean	300	10	0.04	0.38	0.44	0.48	0.51	1	0.18	0.38
POSNEG_RATIO_CLAUSE_coeff_variation	300	10	0.036	0.62	0.73	0.83	0.96	3.1	0.44	0.53
POSNEG_RATIO_CLAUSE_min	300	10	0	0	0	0	0	0	0
POSNEG_RATIO_CLAUSE_max	300	10	1	1	1	1	1	1	0	0
POSNEG_RATIO_CLAUSE_entropy	300	10	0.089	0.87	1.3	1.2	1.5	2.2	0.42	0.35
VCG_CLAUSE_mean	300	10	0	0	0.0001	0.0013	0.0006	0.04	0.0041	3.1
VCG_CLAUSE_coeff_variation	300	10	0.078	0.38	0.63	1.1	1.2	14	1.5	1.3
VCG_CLAUSE_min	300	10	0	0	0.0001	0.00074	0.0002	0.021	0.0023	3.1
VCG_CLAUSE_max	300	10	0	0.0007	0.0024	0.0096	0.0071	0.4	0.029	3
VCG_CLAUSE_entropy	300	10	0.066	0.63	1	1	1.3	2.4	0.52	0.51
UNARY	300	10	0	0	0	0	0	0	0
BINARYp	300	10	0.0097	0.14	0.31	0.43	0.74	0.99	0.33	0.78
TRINARYp	300	10	0.0098	0.62	0.8	0.74	0.94	1	0.24	0.32
VCG_VAR_mean	300	10	0	0	0.0001	0.0013	0.0006	0.04	0.0041	3.1
VCG_VAR_coeff_variation	300	10	0	0.74	1.4	1.9	2.2	18	2.1	1.1
VCG_VAR_min	300	10	0	0	0	0.00055	0.0001	0.015	0.002	3.6
VCG_VAR_max	300	10	0	0.0007	0.0033	0.007	0.0091	0.093	0.011	1.6
VCG_VAR_entropy	300	10	0	2.1	2.6	2.7	3.1	5.7	1	0.38
POSNEG_RATIO_VAR_mean	300	10	0	0.11	0.19	0.22	0.34	0.63	0.15	0.67
POSNEG_RATIO_VAR_stdev	300	10	0	0.098	0.16	0.17	0.24	0.34	0.088	0.52
POSNEG_RATIO_VAR_min	300	10	0	0	0	0.023	0	0.52	0.088	3.9
POSNEG_RATIO_VAR_max	300	10	0	0.73	0.9	0.82	0.99	1	0.22	0.27
POSNEG_RATIO_VAR_entropy	300	10	0	1.7	2.3	2.2	2.9	4.3	0.93	0.42
HORNY_VAR_mean	300	10	0	0	0.0001	0.0006	0.0002	0.017	0.0018	3
HORNY_VAR_coeff_variation	300	10	0.0032	0.83	1.4	2	2.4	24	2.2	1.1
HORNY_VAR_min	300	10	0	0	0	0.00017	0	0.0052	0.00062	3.6
HORNY_VAR_max	300	10	0	0.00052	0.0014	0.0042	0.0048	0.076	0.0075	1.8
HORNY_VAR_entropy	300	10	0.58	1.9	2.3	2.4	2.7	5.1	0.82	0.34
horn_clauses_fraction	300	10	0.01	0.48	0.6	0.66	0.93	1	0.25	0.37
VG_mean	300	10	0	0.0001	0.0002	0.0014	0.0004	0.046	0.0053	3.9
VG_coeff_variation	300	10	0.071	0.69	1	1.3	1.7	10	1.2	0.87
VG_min	300	10	0	0	0	0.00063	0.0001	0.038	0.0032	5.1
VG_max	300	10	0	0.0008	0.0025	0.0057	0.0061	0.074	0.01	1.8
CG_mean	300	196	0	0.0001	0.00045	0.005	0.0036	0.067	0.01	2.1
CG_coeff_variation	300	196	0	0.53	0.71	0.79	0.94	2.1	0.4	0.51
CG_min	300	196	0	0	0.0001	0.0013	0.0007	0.018	0.0034	2.6
CG_max	300	196	0	0.00078	0.0046	0.028	0.033	0.5	0.063	2.2
CG_entropy	300	196	0	3.1	3.7	3.5	3.9	5.3	0.95	0.27
cluster_coeff_mean	300	196	0	0.14	0.17	0.2	0.26	0.5	0.087	0.43
cluster_coeff_coeff_variation	300	196	0	0.31	0.47	0.48	0.65	0.9	0.2	0.42
cluster_coeff_min	300	196	0	0.0095	0.018	0.041	0.03	0.27	0.061	1.5
cluster_coeff_max	300	196	0	0.5	0.59	0.57	0.67	0.9	0.14	0.24
cluster_coeff_entropy	300	196	0	2.9	3.1	3	3.3	3.8	0.58	0.19
DIAMETER_mean	300	10	0	5.5	8.8	20	17	1.8e+02	29	1.5
DIAMETER_coeff_variation	300	10	0	0.011	0.06	0.062	0.091	0.74	0.067	1.1
DIAMETER_min	300	10	0	5	7	18	15	1.8e+02	29	1.6
DIAMETER_max	300	10	0	6	10	21	19	1.8e+02	29	1.4
DIAMETER_entropy	300	10	0	0.41	0.69	0.72	0.96	3.7	0.56	0.78
cl_num_mean	300	10	0	0	2.4e+02	6.2e+02	8.9e+02	4.9e+03	9.4e+02	1.5
cl_num_coeff_variation	300	10	0	0	0.16	0.27	0.4	2.3	0.37	1.4
cl_num_min	300	10	0	0	66	4.5e+02	5.5e+02	4.8e+03	8.6e+02	1.9
cl_num_max	300	10	0	0	4e+02	8.5e+02	1.3e+03	4.9e+03	1.1e+03	1.3
cl_num_q90	300	10	0	0	3.6e+02	8.2e+02	1.3e+03	4.9e+03	1.1e+03	1.3
cl_num_q10	300	10	0	0	91	4.7e+02	6e+02	4.8e+03	8.5e+02	1.8
cl_num_q75	300	10	0	0	2.9e+02	7.1e+02	1e+03	4.9e+03	1e+03	1.4
cl_num_q25	300	10	0	0	1.4e+02	5.3e+02	6.8e+02	4.8e+03	8.9e+02	1.7
cl_num_q50	300	10	0	0	2.3e+02	6.3e+02	8.6e+02	4.9e+03	9.5e+02	1.5
cl_size_mean	300	10	0	0	14	30	29	8.3e+02	75	2.5
cl_size_coeff_variation	300	10	0	0	0.11	0.21	0.26	2.2	0.34	1.6
cl_size_min	300	10	0	0	8	20	22	8.3e+02	60	2.9
cl_size_max	300	10	0	0	22	47	38	1.3e+03	1.2e+02	2.6
cl_size_q90	300	10	0	0	21	46	36	1.3e+03	1.2e+02	2.6
cl_size_q10	300	10	0	0	8.4	21	22	8.3e+02	61	2.9
cl_size_q75	300	10	0	0	17	36	34	8.3e+02	91	2.5
cl_size_q25	300	10	0	0	10	24	24	8.3e+02	65	2.7
cl_size_q50	300	10	0	0	13	28	29	8.3e+02	72	2.6
SP_bias_mean	300	10	0.023	0.29	0.52	0.52	0.76	0.99	0.26	0.5
SP_bias_coeff_variation	300	10	0.0015	0.31	0.54	0.59	0.81	1.9	0.39	0.66
SP_bias_min	300	10	0	0	0	0.031	0.0001	0.8	0.13	4.3
SP_bias_max	300	10	0.19	0.98	1	0.94	1	1	0.15	0.16
SP_bias_q90	300	10	0.091	0.59	0.85	0.76	0.96	1	0.23	0.3
SP_bias_q10	300	10	0	0.022	0.069	0.23	0.37	0.98	0.29	1.3
SP_bias_q75	300	10	0.036	0.53	0.74	0.69	0.94	1	0.27	0.39
SP_bias_q25	300	10	0	0.094	0.27	0.37	0.68	1	0.32	0.87
SP_bias_q50	300	10	0.0016	0.2	0.58	0.55	0.85	1	0.33	0.6
SP_unconstraint_mean	300	10	0	0.033	0.054	0.067	0.084	0.45	0.058	0.87
SP_unconstraint_coeff_variation	300	10	0	0.73	0.93	1.2	1.3	14	1.1	0.91
SP_unconstraint_min	300	10	0	0	0	0.0035	0	0.22	0.024	7
SP_unconstraint_max	300	10	0	0.21	0.29	0.36	0.5	1	0.23	0.62
SP_unconstraint_q90	300	10	0	0.056	0.13	0.16	0.24	0.5	0.12	0.77
SP_unconstraint_q10	300	10	0	0	0.0017	0.011	0.013	0.31	0.03	2.6
SP_unconstraint_q75	300	10	0	0.038	0.068	0.1	0.13	0.5	0.095	0.95
SP_unconstraint_q25	300	10	0	0.0016	0.015	0.025	0.027	0.49	0.05	2.1
SP_unconstraint_q50	300	10	0	0.0097	0.031	0.046	0.064	0.5	0.064	1.4
saps_BestSolution_Mean	300	10	0	2.9e+02	1.9e+03	1.5e+05	4.7e+04	2.4e+06	4.1e+05	2.8
saps_BestSolution_CoeffVariance	300	10	0	0	0.17	0.69	1.1	10	1.3	1.8
saps_FirstLocalMinStep_Mean	300	10	0	0	5e+02	2.3e+03	4.1e+03	1.5e+04	3.1e+03	1.3
saps_FirstLocalMinStep_CoeffVariance	300	10	0	0	0.011	0.21	0.22	1.4	0.38	1.8
saps_FirstLocalMinStep_Median	300	10	0	0	5.2e+02	2.5e+03	4.5e+03	1.5e+04	3.3e+03	1.3
saps_FirstLocalMinStep_Q10	300	10	0	0	0	1.4e+03	7e+02	1.5e+04	2.9e+03	2.1
saps_FirstLocalMinStep_Q90	300	10	0	0	2.2e+02	2.2e+03	4.1e+03	1.5e+04	3.3e+03	1.5
saps_BestAvgImprovement_Mean	300	10	0.38	0.99	3.4	99	11	4.6e+03	4.9e+02	4.9
saps_BestAvgImprovement_CoeffVariance	300	10	0	0	0.17	0.31	0.52	1.8	0.4	1.3
saps_FirstLocalMinRatio_Mean	300	10	0.73	0.91	1	2.4	1.8	31	3.9	1.6
saps_FirstLocalMinRatio_CoeffVariance	300	10	0	0	0.0083	0.085	0.074	1.4	0.17	2
gsat_BestSolution_Mean	300	10	0	3.7e+02	1.4e+03	8e+04	7.2e+03	1.7e+06	2.7e+05	3.5
gsat_BestSolution_CoeffVariance	300	10	0	0.016	0.13	0.83	0.62	1e+02	5.9	7.1
gsat_FirstLocalMinStep_Mean	300	10	0	1.8e+02	3.9e+03	8.3e+03	9.9e+03	8.5e+04	1.3e+04	1.5
gsat_FirstLocalMinStep_CoeffVariance	300	10	0	0.00015	0.012	0.18	0.17	1.4	0.34	1.9
gsat_FirstLocalMinStep_Median	300	10	0	1.8e+02	4e+03	8.7e+03	1.1e+04	8.5e+04	1.3e+04	1.5
gsat_FirstLocalMinStep_Q10	300	10	0	0	5.9e+02	6.2e+03	6.3e+03	8.5e+04	1.2e+04	2
gsat_FirstLocalMinStep_Q90	300	10	0	65	3.5e+03	7.7e+03	9.1e+03	8.5e+04	1.2e+04	1.6
gsat_BestAvgImprovement_Mean	300	10	0.12	0.45	1.3	68	4.1	3.9e+03	4e+02	5.9
gsat_BestAvgImprovement_CoeffVariance	300	10	0	0.096	0.35	0.59	1	3	0.62	1
gsat_FirstLocalMinRatio_Mean	300	10	0.5	0.9	0.97	1.6	1	1.1e+02	7.1	4.3
gsat_FirstLocalMinRatio_CoeffVariance	300	10	0	0.00035	0.0095	0.091	0.049	1.7	0.24	2.7
lobjois_mean_depth_over_vars	300	10	0.0095	0.078	0.2	0.24	0.33	0.97	0.19	0.8
lobjois_log_num_nodes_over_vars	300	10	0.013	0.28	0.53	0.51	0.7	1	0.26	0.52

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	97	3.3	0	0	0.19	3.5	0.03
CG	2	35	3	62	0	49	2.8e+02	0.03
DIAMETER	2	97	3.3	0	0	1.9	3.4	0.033
KLB	2	97	3.3	0	0	79	3e+03	0.03
Pre	1	97	3.3	0	0	11	3.4e+02	0.01
cl	2	97	3.3	0	0	1.9	2	0.033
lobjois	2	97	3.3	0	1.5	2	3.5	0.033
ls_gsat	2	97	3.3	0	1	3	14	0.033
ls_saps	2	97	3.3	0	1.1	2.9	14	0.033
sp	2	97	3.3	0	0	12	4.7e+02	0.033

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	9	./SAT07/industrial/babic/dspam/dspam_dump_vc949.cnf +++++++ ./SAT07/industrial/babic/hsatv17/hsat_vc12062.cnf +++++++ ./SAT09/APPLICATIONS/c32sat/post-cbmc-zfcp-2.8-u2-noholes.cnf +++++++ ./SAT11/application/jarvisalo/smtqfbv-aigs/smtlib-qfbv-aigs-ext_con_032_008_0256-tseitin.cnf +++++++ ./SAT11/application/jarvisalo/smtqfbv-aigs/smtlib-qfbv-aigs-lfsr_004_127_112-tseitin.cnf +++++++ ...