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	296	0	20	2.2e+02	7.6e+02	2.6e+03	1.9e+03	6.4e+04	8.3e+03	3.2
nclausesOrig	296	0	1e+02	2.9e+03	2.9e+04	1e+05	8.6e+04	1.7e+06	2e+05	2
nvars	296	0	20	2.2e+02	6.1e+02	1.8e+03	1.5e+03	3.4e+04	4.7e+03	2.7
nclauses	296	0	1e+02	2.6e+03	2.7e+04	9.6e+04	8.3e+04	1.7e+06	1.9e+05	2
reducedVars	296	0	0	0	0.032	0.36	0.14	54	3.1	8.8
reducedClauses	296	0	0	0	0.0091	0.28	0.024	55	3.2	12
vars_clauses_ratio	296	0	0.0006	0.0096	0.023	0.097	0.15	0.51	0.13	1.3
POSNEG_RATIO_CLAUSE_mean	296	0	0.24	0.48	0.99	0.75	1	1	0.29	0.38
POSNEG_RATIO_CLAUSE_coeff_variation	296	0	0	0	0.024	0.35	0.8	1.1	0.41	1.2
POSNEG_RATIO_CLAUSE_min	296	0	0	0	0.8	0.53	1	1	0.45	0.85
POSNEG_RATIO_CLAUSE_max	296	0	1	1	1	1	1	1	0	0
POSNEG_RATIO_CLAUSE_entropy	296	0	0	0	0.24	0.59	1.1	2.9	0.67	1.1
VCG_CLAUSE_mean	296	0	0.0001	0.0025	0.0058	0.017	0.018	0.35	0.033	2
VCG_CLAUSE_coeff_variation	296	0	0	0.36	0.81	0.97	1.6	2.8	0.75	0.77
VCG_CLAUSE_min	296	0	0.0001	0.0013	0.0033	0.011	0.011	0.35	0.028	2.7
VCG_CLAUSE_max	296	0	0.0001	0.018	0.039	0.049	0.071	0.35	0.044	0.88
VCG_CLAUSE_entropy	296	0	0	0.19	0.31	0.46	0.6	2.6	0.45	0.98
UNARY	296	0	0	0	0	0	0	0	0
BINARYp	296	0	0	0.0037	0.24	0.46	0.94	0.99	0.45	0.98
TRINARYp	296	0	0	0.098	0.89	0.64	0.95	1	0.4	0.63
VCG_VAR_mean	296	0	0.0001	0.0025	0.0058	0.017	0.018	0.35	0.033	2
VCG_VAR_coeff_variation	296	0	0	0.0066	0.18	0.38	0.26	4.6	0.72	1.9
VCG_VAR_min	296	0	0	0.0009	0.0033	0.013	0.012	0.33	0.03	2.4
VCG_VAR_max	296	0	0.0003	0.0043	0.011	0.03	0.028	0.71	0.063	2.1
VCG_VAR_entropy	296	0	0	0.039	3	2.8	4.9	6.6	2.2	0.8
POSNEG_RATIO_VAR_mean	296	0	0	0.032	0.18	0.2	0.32	0.94	0.19	0.94
POSNEG_RATIO_VAR_stdev	296	0	0	0	0.049	0.075	0.095	0.42	0.083	1.1
POSNEG_RATIO_VAR_min	296	0	0	0	0.047	0.075	0.12	0.5	0.094	1.3
POSNEG_RATIO_VAR_max	296	0	0	0.085	0.34	0.43	0.74	1	0.34	0.78
POSNEG_RATIO_VAR_entropy	296	0	0	0	2.6	1.8	2.9	4.2	1.4	0.79
HORNY_VAR_mean	296	0	0	0.0011	0.0026	0.0053	0.0073	0.13	0.0095	1.8
HORNY_VAR_coeff_variation	296	0	0	0.16	0.28	0.49	0.39	6	0.82	1.7
HORNY_VAR_min	296	0	0	0.0002	0.0008	0.0031	0.002	0.13	0.0093	3
HORNY_VAR_max	296	0	0.0002	0.0023	0.0054	0.012	0.011	0.21	0.028	2.3
HORNY_VAR_entropy	296	0	0	1.4	2.8	2.8	4.6	6.3	1.9	0.68
horn_clauses_fraction	296	0	0.0094	0.32	0.73	0.62	0.93	0.99	0.32	0.52
VG_mean	296	0	0.0001	0.0031	0.0074	0.022	0.017	0.34	0.044	2
VG_coeff_variation	296	0	0	0	0.072	0.24	0.21	2.1	0.43	1.8
VG_min	296	0	0	0.0012	0.005	0.021	0.016	0.33	0.043	2.1
VG_max	296	0	0.0002	0.005	0.01	0.027	0.023	0.37	0.047	1.7
CG_mean	296	181	0	0.01	0.021	0.038	0.043	0.32	0.048	1.3
CG_coeff_variation	296	181	0.0057	0.19	0.65	0.8	1.1	4.7	0.79	0.99
CG_min	296	181	0	0.0023	0.013	0.02	0.024	0.2	0.029	1.5
CG_max	296	181	0.0014	0.035	0.069	0.096	0.13	0.37	0.083	0.86
CG_entropy	296	181	0.044	0.42	0.82	1.6	2.9	5.9	1.5	0.95
cluster_coeff_mean	296	181	0.0097	0.077	0.18	0.21	0.35	0.59	0.16	0.73
cluster_coeff_coeff_variation	296	181	0.008	0.16	0.29	0.32	0.34	1.6	0.27	0.85
cluster_coeff_min	296	181	0.0004	0.0098	0.043	0.097	0.15	0.4	0.12	1.2
cluster_coeff_max	296	181	0.041	0.095	0.33	0.36	0.54	0.98	0.28	0.77
cluster_coeff_entropy	296	181	0.098	0.39	0.77	1.2	2	3.9	1.1	0.87
DIAMETER_mean	296	0	2	2	3	9.7	4.5	7.5e+02	62	6.4
DIAMETER_coeff_variation	296	0	0	0	0.0056	0.045	0.083	0.19	0.056	1.3
DIAMETER_min	296	0	2	2	3	8.9	4	7.4e+02	61	6.8
DIAMETER_max	296	0	2	2	3	11	5	7.6e+02	64	6.1
DIAMETER_entropy	296	0	0	0	0.017	0.29	0.44	4.5	0.58	2
cl_num_mean	296	0	0	3.7e+02	1.6e+03	2.1e+03	4e+03	4.9e+03	1.8e+03	0.85
cl_num_coeff_variation	296	0	0	0.015	0.24	0.39	0.65	2.4	0.45	1.1
cl_num_min	296	0	0	73	4.8e+02	1.7e+03	3.8e+03	4.9e+03	1.9e+03	1.1
cl_num_max	296	0	0	9e+02	3.5e+03	2.8e+03	4.5e+03	4.9e+03	1.8e+03	0.63
cl_num_q90	296	0	0	6e+02	3.3e+03	2.7e+03	4.5e+03	4.9e+03	1.8e+03	0.67
cl_num_q10	296	0	0	1.1e+02	5.2e+02	1.7e+03	3.8e+03	4.9e+03	1.9e+03	1.1
cl_num_q75	296	0	0	4e+02	2.3e+03	2.3e+03	4.2e+03	4.9e+03	1.8e+03	0.79
cl_num_q25	296	0	0	1.9e+02	8.4e+02	1.9e+03	4e+03	4.9e+03	1.9e+03	1
cl_num_q50	296	0	0	3e+02	1.6e+03	2.1e+03	4.1e+03	4.9e+03	1.9e+03	0.89
cl_size_mean	296	0	0	25	37	47	66	2.3e+02	35	0.74
cl_size_coeff_variation	296	0	0	0.046	0.097	0.13	0.16	0.91	0.14	1.1
cl_size_min	296	0	0	19	34	40	54	2.3e+02	31	0.78
cl_size_max	296	0	0	29	46	60	84	3.9e+02	45	0.76
cl_size_q90	296	0	0	28	43	56	79	3.9e+02	43	0.77
cl_size_q10	296	0	0	20	34	40	55	2.3e+02	31	0.77
cl_size_q75	296	0	0	26	40	52	72	3.9e+02	41	0.79
cl_size_q25	296	0	0	22	35	43	58	2.3e+02	32	0.74
cl_size_q50	296	0	0	24	38	48	63	3.9e+02	39	0.82
SP_bias_mean	296	0	0	0.35	0.71	0.59	0.84	0.98	0.31	0.54
SP_bias_coeff_variation	296	0	0	0.012	0.083	0.38	0.33	8.4	0.78	2.1
SP_bias_min	296	0	0	0.00047	0.5	0.4	0.74	0.94	0.34	0.87
SP_bias_max	296	0	0	0.58	0.89	0.75	0.98	1	0.3	0.39
SP_bias_q90	296	0	0	0.46	0.79	0.66	0.91	1	0.31	0.47
SP_bias_q10	296	0	0	0.1	0.62	0.51	0.79	0.97	0.33	0.65
SP_bias_q75	296	0	0	0.42	0.74	0.63	0.89	1	0.33	0.52
SP_bias_q25	296	0	0	0.2	0.66	0.55	0.82	0.99	0.33	0.61
SP_bias_q50	296	0	0	0.35	0.7	0.59	0.86	1	0.33	0.57
SP_unconstraint_mean	296	0	0	0	0.015	0.11	0.23	0.5	0.15	1.4
SP_unconstraint_coeff_variation	296	0	0	0.016	0.92	2.4	3.7	16	3.4	1.4
SP_unconstraint_min	296	0	0	0	0	0.07	0.06	0.5	0.13	1.9
SP_unconstraint_max	296	0	0	0.0001	0.034	0.19	0.33	1	0.26	1.3
SP_unconstraint_q90	296	0	0	0	0.029	0.13	0.24	0.99	0.18	1.3
SP_unconstraint_q10	296	0	0	0	0.0004	0.084	0.15	0.5	0.14	1.6
SP_unconstraint_q75	296	0	0	0	0.019	0.12	0.23	0.94	0.17	1.4
SP_unconstraint_q25	296	0	0	0	0.0031	0.1	0.22	0.5	0.15	1.5
SP_unconstraint_q50	296	0	0	0	0.0064	0.11	0.23	0.5	0.16	1.4
saps_BestSolution_Mean	296	0	0	7	16	5.2e+02	47	4.7e+04	3.3e+03	6.2
saps_BestSolution_CoeffVariance	296	0	0	0.21	0.43	3.8	3.6	55	8.4	2.2
saps_FirstLocalMinStep_Mean	296	0	0	65	1.6e+02	4.7e+02	5e+02	6.6e+03	9.3e+02	2
saps_FirstLocalMinStep_CoeffVariance	296	0	0	0.068	0.097	0.12	0.15	0.87	0.092	0.77
saps_FirstLocalMinStep_Median	296	0	0	65	1.6e+02	4.9e+02	5e+02	6.8e+03	9.7e+02	2
saps_FirstLocalMinStep_Q10	296	0	0	49	1.4e+02	4.2e+02	4e+02	6.6e+03	8.9e+02	2.1
saps_FirstLocalMinStep_Q90	296	0	0	73	1.7e+02	5e+02	5.2e+02	6.8e+03	9.8e+02	1.9
saps_BestAvgImprovement_Mean	296	0	0.2	1.6	7.2	19	28	1.7e+02	25	1.3
saps_BestAvgImprovement_CoeffVariance	296	0	0	0.13	0.2	0.22	0.26	1.3	0.16	0.7
saps_FirstLocalMinRatio_Mean	296	0	0.68	0.93	0.99	0.96	1	1.3	0.078	0.081
saps_FirstLocalMinRatio_CoeffVariance	296	0	0	0.0032	0.027	0.065	0.065	1.1	0.14	2.1
gsat_BestSolution_Mean	296	0	0	5.2	20	2.7e+02	52	2.1e+04	1.4e+03	5.2
gsat_BestSolution_CoeffVariance	296	0	0	0.14	0.24	2.8	1.1	59	8.2	3
gsat_FirstLocalMinStep_Mean	296	0	2.7	65	1.6e+02	4.9e+02	5e+02	6.8e+03	9.6e+02	2
gsat_FirstLocalMinStep_CoeffVariance	296	0	0.0014	0.05	0.089	0.11	0.13	1.4	0.13	1.2
gsat_FirstLocalMinStep_Median	296	0	3	65	1.6e+02	5e+02	5.1e+02	6.9e+03	9.9e+02	2
gsat_FirstLocalMinStep_Q10	296	0	0	50	1.4e+02	4.1e+02	4.1e+02	6.5e+03	8.1e+02	2
gsat_FirstLocalMinStep_Q90	296	0	0	72	1.7e+02	4.8e+02	4.8e+02	6.9e+03	9.2e+02	1.9
gsat_BestAvgImprovement_Mean	296	0	0.044	0.98	6.5	20	32	1.6e+02	27	1.4
gsat_BestAvgImprovement_CoeffVariance	296	0	0.02	0.16	0.26	0.34	0.38	5.9	0.42	1.3
gsat_FirstLocalMinRatio_Mean	296	0	0.69	0.91	0.99	0.98	1	8.5	0.44	0.45
gsat_FirstLocalMinRatio_CoeffVariance	296	0	0	0.0016	0.013	0.06	0.054	3.5	0.24	3.9
lobjois_mean_depth_over_vars	296	0	0.027	0.49	0.76	0.66	0.87	1	0.27	0.41
lobjois_log_num_nodes_over_vars	296	0	0.087	0.71	0.89	0.8	0.95	1	0.2	0.25

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	crash	cost_min	cost_mean	cost_max
Basic	2	1e+02	0	0	0.015	0.31
CG	2	39	61	0	40	1.6e+02
DIAMETER	2	1e+02	0	0	1	2.4
KLB	2	1e+02	0	0	0.11	4.2
Pre	1	1e+02	0	0	0.98	38
cl	2	1e+02	0	0	1.8	2
lobjois	2	1e+02	0	0.49	2	2.7
ls_gsat	2	1e+02	0	0.4	2.1	3.4
ls_saps	2	1e+02	0	0.22	2	3.5
sp	2	1e+02	0	0	1.3	8.8

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.

There were no duplicated features.