55335
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":"4","search_strategy_width":"64","nr_threads":"1","alpha":"0.5","beam_seed":"","maximum_subgroups":"100","maximum_time":"1.0","minimum_coverage":"2","nr_bins":"32","numeric_strategy":"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
4
4221
search_strategy_width
64
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
32
4221
numeric_strategy
bins
4221
beta
1.0
4221
Cortana
coverage
openml.evaluation.coverage(1.0)
25
[25, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30]
quality
openml.evaluation.quality(1.0)
0.9943181872367859
[0.9943181872367859, 0.993686854839325, 0.993686854839325, 0.993686854839325, 0.993686854839325, 0.993686854839325, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708]
probability
openml.evaluation.probability(1.0)
0.64
[0.64, 0.6153846153846154, 0.6153846153846154, 0.6153846153846154, 0.6153846153846154, 0.6153846153846154, 0.5925925925925926, 0.5925925925925926, 0.5925925925925926, 0.5925925925925926, 0.5925925925925926, 0.5925925925925926, 0.5925925925925926, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5714285714285714, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5517241379310345, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333]
positives
openml.evaluation.positives(1.0)
16
[16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16]
cortana_quality
openml.evaluation.cortana_quality(1.0)
0.9943181872367859
[0.9943181872367859, 0.993686854839325, 0.993686854839325, 0.993686854839325, 0.993686854839325, 0.993686854839325, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9930555820465088, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9924242496490479, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9917929172515869, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708, 0.9911616444587708]