10418851
10580
Thomas Fan
9946
Supervised Classification
17373
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)
8255503
l2_regularization
0.0
17372
learning_rate
0.1
17372
loss
"auto"
17372
max_bins
255
17372
max_depth
null
17372
max_iter
100
17372
max_leaf_nodes
31
17372
min_samples_leaf
20
17372
n_iter_no_change
null
17372
random_state
53843
17372
scoring
null
17372
tol
1e-07
17372
validation_fraction
0.1
17372
verbose
0
17372
warm_start
false
17372
aggressive_elimination
false
17373
cv
5
17373
error_score
NaN
17373
force_exhaust_resources
true
17373
max_resources
100
17373
min_resources
"auto"
17373
n_candidates
100
17373
n_jobs
3
17373
param_distributions
{"l2_regularization": [0, 0.01, 0.1], "learning_rate": [0.01, 0.1, 1], "max_depth": [5, 6, 7, 8, 9, 1000], "max_leaf_nodes": [30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "min_samples_leaf": [2, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]}
17373
pre_dispatch
"2*n_jobs"
17373
random_state
0
17373
ratio
3
17373
refit
{"oml-python:serialized_object": "function", "value": "sklearn.model_selection._search_successive_halving._refit_callable"}
17373
resource
"max_iter"
17373
return_train_score
true
17373
scoring
null
17373
verbose
1
17373
openml-python
Sklearn_0.23.dev0.
1510
wdbc
https://www.openml.org/data/download/1592318/phpAmSP4g
-1
21760119
description
https://api.openml.org/data/download/21760119/description.xml
-1
21760120
predictions
https://api.openml.org/data/download/21760120/predictions.arff
-1
21760121
trace
https://api.openml.org/data/download/21760121/trace.arff
area_under_roc_curve
0.9952698060356218 [0.99527,0.99527]
average_cost
0
f_measure
0.9701086002622853 [0.976224,0.959811]
kappa
0.9360348624217215
kb_relative_information_score
0.9255135812242378
mean_absolute_error
0.03459342322029008
mean_prior_absolute_error
0.46764379083961705
number_of_instances
569 [357,212]
precision
0.970100571129809 [0.97486,0.962085]
predictive_accuracy
0.9701230228471002
prior_entropy
0.9526357368194003
recall
0.9701230228471002 [0.977591,0.957547]
relative_absolute_error
0.07397387476947007
root_mean_prior_squared_error
0.4834927399189952
root_mean_squared_error
0.1570691344538464
root_relative_squared_error
0.3248634808459831
total_cost
0
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.9973544973544973 [0.997354,0.997354]
area_under_roc_curve
0.9920634920634921 [0.992063,0.992063]
area_under_roc_curve
0.9986772486772487 [0.998677,0.998677]
area_under_roc_curve
0.9986772486772487 [0.998677,0.998677]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.966931216931217 [0.966931,0.966931]
area_under_roc_curve
0.9974025974025974 [0.997403,0.997403]
area_under_roc_curve
0.9935064935064934 [0.993506,0.993506]
area_under_roc_curve
0.998639455782313 [0.998639,0.998639]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
f_measure
1 [1,1]
f_measure
0.9652084757347914 [0.971429,0.954545]
f_measure
0.9823623542652152 [0.986301,0.97561]
f_measure
0.9649122807017544 [0.972222,0.952381]
f_measure
0.9825365904115021 [0.985915,0.976744]
f_measure
0.9823623542652152 [0.986301,0.97561]
f_measure
0.9290184921763869 [0.945946,0.9]
f_measure
0.9823756902902523 [0.985915,0.976744]
f_measure
0.9475718281210272 [0.956522,0.933333]
f_measure
0.9642857142857143 [0.971429,0.952381]
kappa
1
kappa
0.9260700389105059
kappa
0.9619238476953906
kappa
0.9246031746031746
kappa
0.9626719056974459
kappa
0.9619238476953906
kappa
0.8461538461538461
kappa
0.9626719056974459
kappa
0.8898905344494525
kappa
0.9238095238095239
kb_relative_information_score
0.9737521498046315
kb_relative_information_score
0.9157461764114793
kb_relative_information_score
0.9342629173220236
kb_relative_information_score
0.9291536002216053
kb_relative_information_score
0.9519669605836727
kb_relative_information_score
0.941163612604449
kb_relative_information_score
0.8458133489951604
kb_relative_information_score
0.9592371537691278
kb_relative_information_score
0.8763613899342498
kb_relative_information_score
0.9279220211199611
mean_absolute_error
0.013456722165897819
mean_absolute_error
0.03784483949781014
mean_absolute_error
0.031732840215088376
mean_absolute_error
0.03247573694628299
mean_absolute_error
0.02291546351302314
mean_absolute_error
0.02883714632935106
mean_absolute_error
0.06969672738228276
mean_absolute_error
0.019193212632143367
mean_absolute_error
0.05752238412335251
mean_absolute_error
0.03221747611512206
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4665867821919071
mean_prior_absolute_error
0.4710418778996528
mean_prior_absolute_error
0.4710418778996528
mean_prior_absolute_error
0.4682574430823117
number_of_instances
57 [36,21]
number_of_instances
57 [36,21]
number_of_instances
57 [36,21]
number_of_instances
57 [36,21]
number_of_instances
57 [36,21]
number_of_instances
57 [36,21]
number_of_instances
57 [36,21]
number_of_instances
57 [35,22]
number_of_instances
57 [35,22]
number_of_instances
56 [35,21]
precision
1 [1,1]
precision
0.9679633867276888 [1,0.913043]
precision
0.9829302987197724 [0.972973,1]
precision
0.9649122807017544 [0.972222,0.952381]
precision
0.9832535885167464 [1,0.954545]
precision
0.9829302987197724 [0.972973,1]
precision
0.9307479224376731 [0.921053,0.947368]
precision
0.982943469785575 [0.972222,1]
precision
0.9483779781935656 [0.970588,0.913043]
precision
0.9642857142857143 [0.971429,0.952381]
predictive_accuracy
1
predictive_accuracy
0.9649122807017544
predictive_accuracy
0.9824561403508772
predictive_accuracy
0.9649122807017544
predictive_accuracy
0.9824561403508772
predictive_accuracy
0.9824561403508772
predictive_accuracy
0.9298245614035088
predictive_accuracy
0.9824561403508772
predictive_accuracy
0.9473684210526316
predictive_accuracy
0.9642857142857143
prior_entropy
0.9495176370074769
prior_entropy
0.9495176370074769
prior_entropy
0.9495176370074769
prior_entropy
0.9495176370074769
prior_entropy
0.9495176370074769
prior_entropy
0.9495176370074769
prior_entropy
0.9495176370074769
prior_entropy
0.9626598502888526
prior_entropy
0.9626598502888526
prior_entropy
0.9544459669879928
recall
1 [1,1]
recall
0.9649122807017544 [0.944444,1]
recall
0.9824561403508771 [1,0.952381]
recall
0.9649122807017544 [0.972222,0.952381]
recall
0.9824561403508771 [0.972222,1]
recall
0.9824561403508771 [1,0.952381]
recall
0.9298245614035088 [0.972222,0.857143]
recall
0.9824561403508771 [1,0.954545]
recall
0.9473684210526315 [0.942857,0.954545]
recall
0.9642857142857143 [0.971429,0.952381]
relative_absolute_error
0.028840770205022803
relative_absolute_error
0.08110996912519601
relative_absolute_error
0.06801058543925204
relative_absolute_error
0.06960277955950694
relative_absolute_error
0.04911297187925484
relative_absolute_error
0.06180446474261747
relative_absolute_error
0.14937570038925044
relative_absolute_error
0.040746297797819464
relative_absolute_error
0.12211734629592032
relative_absolute_error
0.06880291299386516
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4823984047513734
root_mean_prior_squared_error
0.4869941648669064
root_mean_prior_squared_error
0.4869941648669064
root_mean_prior_squared_error
0.4841269273621067
root_mean_squared_error
0.06702178655266645
root_mean_squared_error
0.1586117087592288
root_mean_squared_error
0.1470451040639405
root_mean_squared_error
0.14257170884182233
root_mean_squared_error
0.1333104030403064
root_mean_squared_error
0.13224848977105036
root_mean_squared_error
0.24551708863550772
root_mean_squared_error
0.1328051608944432
root_mean_squared_error
0.19760866850128886
root_mean_squared_error
0.15116308970865372
root_relative_squared_error
0.1389345111686455
root_relative_squared_error
0.328798161845035
root_relative_squared_error
0.30482087547475845
root_relative_squared_error
0.295547637466387
root_relative_squared_error
0.27634917886806476
root_relative_squared_error
0.27414785884130527
root_relative_squared_error
0.5089508717634472
root_relative_squared_error
0.2727038031980082
root_relative_squared_error
0.4057721483280904
root_relative_squared_error
0.3122385497793021
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
wall_clock_time_millis
4082.8752517700195
wall_clock_time_millis
4276.91388130188
wall_clock_time_millis
4151.358604431152
wall_clock_time_millis
4086.613893508911
wall_clock_time_millis
4120.087146759033
wall_clock_time_millis
4216.669797897339
wall_clock_time_millis
4337.356805801392
wall_clock_time_millis
4136.651039123535
wall_clock_time_millis
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wall_clock_time_millis
3979.7658920288086
wall_clock_time_millis_testing
0.896453857421875
wall_clock_time_millis_testing
1.0428428649902344
wall_clock_time_millis_testing
0.8909702301025391
wall_clock_time_millis_testing
0.8764266967773438
wall_clock_time_millis_testing
0.9002685546875
wall_clock_time_millis_testing
0.8924007415771484
wall_clock_time_millis_testing
1.0895729064941406
wall_clock_time_millis_testing
1.0006427764892578
wall_clock_time_millis_testing
0.9973049163818359
wall_clock_time_millis_testing
1.032114028930664
wall_clock_time_millis_training
4081.9787979125977
wall_clock_time_millis_training
4275.87103843689
wall_clock_time_millis_training
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wall_clock_time_millis_training
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wall_clock_time_millis_training
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wall_clock_time_millis_training
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wall_clock_time_millis_training
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wall_clock_time_millis_training
4135.650396347046
wall_clock_time_millis_training
4109.626770019531
wall_clock_time_millis_training
3978.733777999878