10418908
10580
Thomas Fan
10101
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.
1464
blood-transfusion-service-center
https://www.openml.org/data/download/1586225/php0iVrYT
-1
21760291
description
https://api.openml.org/data/download/21760291/description.xml
-1
21760292
predictions
https://api.openml.org/data/download/21760292/predictions.arff
-1
21760293
trace
https://api.openml.org/data/download/21760293/trace.arff
area_under_roc_curve
0.7220678099743741 [0.722068,0.722068]
average_cost
0
f_measure
0.7300934782870966 [0.861044,0.310757]
kappa
0.200024727992087
kb_relative_information_score
0.11237497595359144
mean_absolute_error
0.3078659531839886
mean_prior_absolute_error
0.3630445632798566
number_of_instances
748 [570,178]
precision
0.7322434660871405 [0.794074,0.534247]
predictive_accuracy
0.768716577540107
prior_entropy
0.7916465694609683
recall
0.7687165775401069 [0.940351,0.219101]
relative_absolute_error
0.848011468351523
root_mean_prior_squared_error
0.4258399633559147
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0.4024293234738312
root_relative_squared_error
0.9450247935924299
total_cost
0
area_under_roc_curve
0.7422027290448343 [0.742203,0.742203]
area_under_roc_curve
0.8065302144249513 [0.80653,0.80653]
area_under_roc_curve
0.6257309941520468 [0.625731,0.625731]
area_under_roc_curve
0.6647173489278753 [0.664717,0.664717]
area_under_roc_curve
0.8230994152046783 [0.823099,0.823099]
area_under_roc_curve
0.6759259259259259 [0.675926,0.675926]
area_under_roc_curve
0.76364522417154 [0.763645,0.763645]
area_under_roc_curve
0.7305068226120858 [0.730507,0.730507]
area_under_roc_curve
0.7363261093911249 [0.736326,0.736326]
area_under_roc_curve
0.737358101135191 [0.737358,0.737358]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
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0
average_cost
0
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0
average_cost
0
average_cost
0
average_cost
0
f_measure
0.7438482384823847 [0.861789,0.37037]
f_measure
0.7335831381733021 [0.852459,0.357143]
f_measure
0.6630681818181817 [0.84375,0.090909]
f_measure
0.7441490683229813 [0.834783,0.457143]
f_measure
0.8107609005414648 [0.892562,0.551724]
f_measure
0.73344 [0.864,0.32]
f_measure
0.6866372036962636 [0.870229,0.105263]
f_measure
0.7055592469545958 [0.868217,0.190476]
f_measure
0.7351117351117351 [0.873016,0.272727]
f_measure
0.6931421856639247 [0.848,0.173913]
kappa
0.2504409171075837
kappa
0.22413793103448282
kappa
0.003984063745019896
kappa
0.29210134128166926
kappa
0.45193929173693087
kappa
0.21441774491682059
kappa
0.08207343412526993
kappa
0.13087934560327202
kappa
0.187928669410151
kappa
0.06141522029372485
kb_relative_information_score
0.15799379522552992
kb_relative_information_score
0.20817383166448747
kb_relative_information_score
0.025804100404640824
kb_relative_information_score
0.08663463419378893
kb_relative_information_score
0.24211314791836372
kb_relative_information_score
0.0876553778100879
kb_relative_information_score
0.08214314557478913
kb_relative_information_score
0.0623426968118159
kb_relative_information_score
0.10366902198887827
kb_relative_information_score
0.06528596208998416
mean_absolute_error
0.291298922031214
mean_absolute_error
0.28325926291173237
mean_absolute_error
0.31941222117523177
mean_absolute_error
0.31054518032380896
mean_absolute_error
0.27301809848826125
mean_absolute_error
0.3122235775387283
mean_absolute_error
0.32353167119952014
mean_absolute_error
0.32977337533232565
mean_absolute_error
0.31181001443562506
mean_absolute_error
0.3240556586260192
mean_prior_absolute_error
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mean_prior_absolute_error
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mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.35873873873873896
mean_prior_absolute_error
0.35873873873873896
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
74 [57,17]
number_of_instances
74 [57,17]
precision
0.7436363636363637 [0.80303,0.555556]
precision
0.728 [0.8,0.5]
precision
0.6380281690140844 [0.760563,0.25]
precision
0.7419066937119675 [0.827586,0.470588]
precision
0.8157954545454545 [0.84375,0.727273]
precision
0.740672268907563 [0.794118,0.571429]
precision
0.8254054054054054 [0.77027,1]
precision
0.7511111111111112 [0.777778,0.666667]
precision
0.7518213866039952 [0.797101,0.6]
precision
0.6769342872284049 [0.779412,0.333333]
predictive_accuracy
0.7733333333333333
predictive_accuracy
0.76
predictive_accuracy
0.7333333333333333
predictive_accuracy
0.7466666666666667
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
0.7778597106646706
recall
0.7733333333333333 [0.929825,0.277778]
recall
0.76 [0.912281,0.277778]
recall
0.7333333333333333 [0.947368,0.055556]
recall
0.7466666666666667 [0.842105,0.444444]
recall
0.8266666666666667 [0.947368,0.444444]
recall
0.7733333333333333 [0.947368,0.222222]
recall
0.7733333333333333 [1,0.055556]
recall
0.7733333333333333 [0.982456,0.111111]
recall
0.7837837837837838 [0.964912,0.176471]
recall
0.7432432432432432 [0.929825,0.117647]
relative_absolute_error
0.8000373206511293
relative_absolute_error
0.77795681552585
relative_absolute_error
0.8772490328161114
relative_absolute_error
0.8528961668480174
relative_absolute_error
0.749829990721385
relative_absolute_error
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relative_absolute_error
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relative_absolute_error
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relative_absolute_error
0.8691841185925254
relative_absolute_error
0.9033193899419415
root_mean_prior_squared_error
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root_mean_prior_squared_error
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root_mean_prior_squared_error
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root_mean_prior_squared_error
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root_mean_squared_error
0.4044881746141092
root_mean_squared_error
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root_mean_squared_error
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root_mean_squared_error
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root_mean_squared_error
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root_mean_squared_error
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root_mean_squared_error
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root_mean_squared_error
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root_mean_squared_error
0.38624310189128314
root_mean_squared_error
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root_relative_squared_error
0.9470900978028104
root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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root_relative_squared_error
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total_cost
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wall_clock_time_millis
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_testing
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wall_clock_time_millis_training
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