53887
4221
{"search_strategy":"beam","use_nominal_sets":"false","post_processing_count":"20","maximum_coverage_fraction":"1.0","numeric_operators":"<html>≤, ≥<\/html>","overall_ranking_loss":"0.0","post_processing_do_autorun":"true","search_depth":"1","search_strategy_width":"1024","nr_threads":"1","alpha":"0.5","beam_seed":"","maximum_subgroups":"100","maximum_time":"1.0","minimum_coverage":"2","nr_bins":"128","numeric_strategy":"best-bins","beta":"1.0"}
search_strategy
beam
4221
use_nominal_sets
false
4221
post_processing_count
20
4221
maximum_coverage_fraction
1.0
4221
numeric_operators
<html>≤, ≥</html>
4221
overall_ranking_loss
0.0
4221
post_processing_do_autorun
true
4221
search_depth
1
4221
search_strategy_width
1024
4221
nr_threads
1
4221
alpha
0.5
4221
beam_seed
4221
maximum_subgroups
100
4221
maximum_time
1.0
4221
minimum_coverage
2
4221
nr_bins
128
4221
numeric_strategy
best-bins
4221
beta
1.0
4221
Cortana
coverage
openml.evaluation.coverage(1.0)
853
[853, 980, 1158, 1097, 1038, 1099, 1162, 1219, 1341, 1523, 916, 1341, 1098, 1280, 1342, 1280, 1462, 1468, 1770, 1645, 1951, 1828, 1923, 2072, 1462, 2132, 1889, 2132, 2545, 2255, 2438, 1950, 2316, 2587, 2316, 2193, 2635, 2559, 2702, 1280, 2754, 2786, 1890, 2132, 2859, 2965, 2742, 1950, 3035, 2620, 2195, 1829, 2681, 2376, 2623, 2132, 1889, 2075, 2315, 2863, 3229, 2924, 2377, 2080, 2681, 2438, 2315, 2437, 2863, 2438, 2743, 3290, 3413, 2742, 3168, 3290, 3534, 2925, 3169, 2376, 3107, 2622, 3777, 2438, 3518, 3229, 3838, 2560, 2744, 2682, 3229, 2803, 3351, 2441, 3229, 2376, 3535, 3719, 2989, 2925]
quality
openml.evaluation.quality(1.0)
0.9089035391807556
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probability
openml.evaluation.probability(1.0)
0.34583821805392734
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positives
openml.evaluation.positives(1.0)
295
[295, 296, 300, 295, 292, 288, 285, 286, 290, 295, 270, 286, 276, 282, 284, 280, 287, 283, 293, 284, 295, 290, 289, 294, 264, 286, 276, 285, 299, 287, 294, 275, 289, 299, 288, 283, 299, 296, 300, 245, 300, 300, 264, 273, 300, 300, 290, 259, 300, 284, 267, 251, 282, 268, 276, 257, 247, 254, 262, 283, 297, 285, 263, 251, 273, 263, 258, 260, 276, 259, 269, 290, 292, 265, 281, 285, 293, 269, 277, 246, 274, 255, 299, 247, 288, 275, 294, 243, 250, 246, 267, 250, 270, 234, 264, 231, 275, 282, 253, 250]
cortana_quality
openml.evaluation.cortana_quality(1.0)
0.9089035391807556
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