10418916
10580
Thomas Fan
146195
Supervised Classification
17373
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)
8255505
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
145
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
false
17373
max_resources
"auto"
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
"n_samples"
17373
return_train_score
true
17373
scoring
null
17373
verbose
1
17373
openml-python
Sklearn_0.23.dev0.
40668
connect-4
https://www.openml.org/data/download/4965243/connect-4.arff
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21760315
description
https://api.openml.org/data/download/21760315/description.xml
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21760316
predictions
https://api.openml.org/data/download/21760316/predictions.arff
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21760317
trace
https://api.openml.org/data/download/21760317/trace.arff
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average_cost
0
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kappa
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0.23369393252111362
mean_absolute_error
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mean_prior_absolute_error
0.3312661139316681
number_of_instances
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precision
0.7256467863496688 [0.5,0.803834,0.729122]
predictive_accuracy
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prior_entropy
1.2184443574876134
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relative_absolute_error
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total_cost
0
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area_under_roc_curve
0.8771953455125937 [0.792099,0.889002,0.88512]
area_under_roc_curve
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0
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0
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f_measure
0.6866015446443703 [0.003096,0.547891,0.837642]
f_measure
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kb_relative_information_score
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kb_relative_information_score
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kb_relative_information_score
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kb_relative_information_score
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kb_relative_information_score
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kb_relative_information_score
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kb_relative_information_score
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kb_relative_information_score
0.2506939183241844
kb_relative_information_score
0.22487915116141746
kb_relative_information_score
0.2422705709126879
mean_absolute_error
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mean_absolute_error
0.26801235485598435
mean_absolute_error
0.26897112247281585
mean_absolute_error
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mean_absolute_error
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mean_absolute_error
0.2646656608501005
mean_absolute_error
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mean_absolute_error
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mean_absolute_error
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mean_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
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number_of_instances
6756 [645,1663,4448]
number_of_instances
6756 [645,1663,4448]
number_of_instances
6756 [645,1663,4448]
number_of_instances
6756 [645,1664,4447]
number_of_instances
6756 [645,1664,4447]
number_of_instances
6756 [645,1664,4447]
number_of_instances
6756 [645,1664,4447]
number_of_instances
6755 [644,1664,4447]
number_of_instances
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number_of_instances
6755 [645,1663,4447]
precision
0.7761852612872369 [1,0.814672,0.729341]
precision
0.6792038968499577 [0,0.808729,0.72925]
precision
0.775655467003017 [1,0.796105,0.735464]
precision
0.6885278275912502 [0,0.827711,0.736158]
predictive_accuracy
0.7356423919478982
predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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prior_entropy
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prior_entropy
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prior_entropy
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prior_entropy
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recall
0.7356423919478982 [0,0.359591,0.982914]
recall
0.7391947898164595 [0.00155,0.380637,0.980216]
recall
0.7307578448786264 [0,0.361996,0.974595]
recall
0.7283895796329188 [0,0.336538,0.980661]
recall
0.7383066903493192 [0,0.378606,0.979987]
recall
0.7433392539964476 [0.00155,0.417668,0.972791]
recall
0.7341622261693309 [0,0.369591,0.977063]
recall
0.7472982975573649 [0,0.412861,0.980661]
recall
0.7366395262768319 [0,0.375225,0.978637]
recall
0.7438934122871946 [0,0.388455,0.984709]
relative_absolute_error
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relative_absolute_error
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relative_absolute_error
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total_cost
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wall_clock_time_millis
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