53887
4221
{"search_strategy":"beam","use_nominal_sets":"false","post_processing_count":"20","maximum_coverage_fraction":"1.0","numeric_operators":"=","overall_ranking_loss":"0.0","post_processing_do_autorun":"true","search_depth":"3","search_strategy_width":"16","nr_threads":"1","alpha":"0.5","beam_seed":"","maximum_subgroups":"100","maximum_time":"1.0","minimum_coverage":"2","nr_bins":"2","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
=
4221
overall_ranking_loss
0.0
4221
post_processing_do_autorun
true
4221
search_depth
3
4221
search_strategy_width
16
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
2
4221
numeric_strategy
best-bins
4221
beta
1.0
4221
Cortana
coverage
openml.evaluation.coverage(1.0)
156
[156, 110, 102, 153, 208, 197, 135, 317, 230, 143, 241, 366, 295, 281, 95, 307, 294, 141, 69, 111, 233, 158, 158, 220, 310, 252, 172, 200, 209, 396, 377, 226, 198, 213, 174, 332, 152, 209, 314, 287, 191, 118, 253, 212, 344, 103, 242, 270, 309, 402, 125, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 9, 11, 356, 126, 2, 2, 2, 2, 2, 2]
quality
openml.evaluation.quality(1.0)
0.16986127197742462
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probability
openml.evaluation.probability(1.0)
0.3525641025641026
[0.3525641025641026, 0.4727272727272727, 0.5, 0.3333333333333333, 0.25, 0.2436548223350254, 0.31851851851851853, 0.15772870662460567, 0.18695652173913044, 0.2727272727272727, 0.17427385892116182, 0.12568306010928962, 0.14576271186440679, 0.1494661921708185, 0.35789473684210527, 0.13029315960912052, 0.1326530612244898, 0.23404255319148937, 0.42028985507246375, 0.2702702702702703, 0.1459227467811159, 0.189873417721519, 0.17088607594936708, 0.1318181818181818, 0.1032258064516129, 0.10714285714285714, 0.13372093023255813, 0.12, 0.11483253588516747, 0.07575757575757576, 0.07692307692307693, 0.10176991150442478, 0.10101010101010101, 0.09389671361502347, 0.10344827586206896, 0.07228915662650602, 0.1118421052631579, 0.09090909090909091, 0.07006369426751592, 0.06968641114982578, 0.07853403141361257, 0.1016949152542373, 0.06719367588932806, 0.07075471698113207, 0.05813953488372093, 0.0970873786407767, 0.06198347107438017, 0.05925925925925926, 0.05501618122977346, 0.0472636815920398, 0.064, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.5, 0.42857142857142855, 0.3333333333333333, 0.2727272727272727, 0.0449438202247191, 0.05555555555555555, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
positives
openml.evaluation.positives(1.0)
55
[55, 52, 51, 51, 52, 48, 43, 50, 43, 39, 42, 46, 43, 42, 34, 40, 39, 33, 29, 30, 34, 30, 27, 29, 32, 27, 23, 24, 24, 30, 29, 23, 20, 20, 18, 24, 17, 19, 22, 20, 15, 12, 17, 15, 20, 10, 15, 16, 17, 19, 8, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 16, 7, 2, 2, 2, 2, 2, 2]
cortana_quality
openml.evaluation.cortana_quality(1.0)
0.16986127197742462
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