Overview of Feature Values

The following measures were taken for the results of each feature:
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 4.0e+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 ok timeout memout presolved crash other unknown cost_min cost_mean cost_max cost_na
Pre 115 97 0 0 3.3 0 0 0 0 11 3.4e+02 0.01
Basic 14 97 0 0 3.3 0 0 0 0 0.19 3.5 0.03
KLB 20 97 0 0 3.3 0 0 0 0 79 3e+03 0.03
CG 10 35 0 0 3 62 0 0 0 49 2.8e+02 0.03
DIAMETER 5 97 0 0 3.3 0 0 0 0 1.9 3.4 0.033
cl 18 97 0 0 3.3 0 0 0 0 1.9 2 0.033
sp 18 97 0 0 3.3 0 0 0 0 12 4.7e+02 0.033
ls_saps 11 97 0 0 3.3 0 0 0 1.1 2.9 14 0.033
ls_gsat 11 97 0 0 3.3 0 0 0 1 3 14 0.033
lobjois 2 97 0 0 3.3 0 0 0 1.5 2 3.5 0.033

Duplicated Features

Underneath, you'll find blocks of duplicated 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 +++++++ ...