10578761
28997
Marc Boel
28
Supervised Classification
19037
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(1)
8295043
Python_3.8.10. Sklearn_0.24.2. NumPy_1.17.4. SciPy_1.3.3.
add_indicator
false
18819
copy
true
18819
fill_value
null
18819
missing_values
NaN
18819
strategy
"mean"
18819
verbose
0
18819
n_jobs
null
18996
remainder
"drop"
18996
sparse_threshold
0.3
18996
transformer_weights
null
18996
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}]
18996
verbose
false
18996
categories
"auto"
18997
drop
null
18997
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
18997
handle_unknown
"ignore"
18997
sparse
true
18997
memory
null
19037
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
19037
verbose
false
19037
ccp_alpha
0.0
19038
criterion
"friedman_mse"
19038
init
null
19038
learning_rate
0.49398513943468425
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
2043
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
196
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
8
19038
random_state
51751
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.06379074643649442
19038
verbose
0
19038
warm_start
false
19038
openml-python
Sklearn_0.24.2.
28
optdigits
https://www.openml.org/data/download/28/dataset_28_optdigits.arff
-1
22083789
description
https://api.openml.org/data/download/22083789/description.xml
-1
22083790
predictions
https://api.openml.org/data/download/22083790/predictions.arff
area_under_roc_curve
0.9995455713985041 [0.99996,0.999638,0.999846,0.999557,0.999738,0.998867,0.999772,0.999907,0.999485,0.998684]
average_cost
0
f_measure
0.9818636863543444 [0.992767,0.981691,0.991039,0.979592,0.98326,0.981267,0.990135,0.98326,0.979223,0.956676]
kappa
0.9798337157518542
kb_relative_information_score
0.9808978608961221
mean_absolute_error
0.004617598831013391
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9818505338078292 [0.990975,0.985989,0.992819,0.965035,0.982394,0.985663,0.989247,0.985866,0.978339,0.962633]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.981940342505429 [0.994565,0.977431,0.989267,0.994595,0.984127,0.976909,0.991023,0.980668,0.980108,0.950791]
predictive_accuracy
0.9818505338078292
prior_entropy
3.3218327251668773
relative_absolute_error
0.025653703403251713
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.05423977397297207
root_relative_squared_error
0.18080057590160017
total_cost
0
unweighted_recall
0.9818961144831994 [0.990975,0.985989,0.992819,0.965035,0.982394,0.985663,0.989247,0.985866,0.978339,0.962633]
area_under_roc_curve
0.9995141627802304 [1,0.999896,0.999859,0.999932,0.997151,1,0.999682,0.999824,0.999677,0.999153]
area_under_roc_curve
0.9998168408663505 [1,1,1,0.999282,0.999896,0.999929,1,1,0.999928,0.999153]
area_under_roc_curve
0.999894427784106 [1,1,1,0.999757,0.999861,1,1,1,1,0.999329]
area_under_roc_curve
0.9997958537374657 [1,0.999861,0.999929,0.999166,1,1,1,0.999965,0.999928,0.999118]
area_under_roc_curve
0.999905032723576 [0.999892,1,1,1,1,0.999857,1,1,0.999821,0.999479]
area_under_roc_curve
0.9993777542354368 [0.999964,0.999896,1,0.99934,0.999792,0.997812,0.999682,0.999931,0.998745,0.998576]
area_under_roc_curve
0.9998170503763182 [0.999894,0.999792,1,0.999861,1,1,0.999964,0.999861,0.999929,0.998871]
area_under_roc_curve
0.999633877951076 [1,0.998923,0.999964,0.999583,0.999896,0.999435,1,0.999548,0.999753,0.999259]
area_under_roc_curve
0.9989728118718038 [1,0.998632,0.998817,0.999826,1,0.997141,1,0.999859,0.998941,0.996506]
area_under_roc_curve
0.9998733704408659 [0.999965,0.999826,1,1,0.999894,0.999859,0.999647,1,0.999753,0.999788]
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
0.9750995883248879 [0.990826,0.974359,0.973451,0.982456,0.964286,1,0.964912,0.973451,0.972477,0.954955]
f_measure
0.9840580681153328 [1,0.99115,1,0.964286,0.982456,0.982456,1,0.990991,0.981818,0.948276]
f_measure
0.9910981799551456 [1,1,1,0.982456,0.982456,1,1,0.974359,1,0.972477]
f_measure
0.9838870262933754 [1,0.973913,0.981818,0.982143,0.991304,0.99115,0.99115,0.991304,0.990991,0.945455]
f_measure
0.9911032025753629 [0.990826,0.991304,1,1,1,0.972973,0.990991,1,0.990991,0.973451]
f_measure
0.9770033392189871 [0.990826,0.982759,1,0.982143,0.973913,0.953271,0.990991,0.99115,0.963636,0.941176]
f_measure
0.9840625439192126 [0.990991,0.982143,0.990991,0.99115,0.991304,0.982456,0.990826,0.982456,0.990991,0.947368]
f_measure
0.9713725181012854 [0.99115,0.964286,0.990991,0.944444,0.973451,0.955752,1,0.956522,0.973913,0.964912]
f_measure
0.9786922683112532 [0.99115,0.982759,0.981818,0.973913,0.990991,0.990991,1,0.972973,0.954955,0.947368]
f_measure
0.9821845088388147 [0.982143,0.974359,0.99115,0.99115,0.982143,0.982456,0.972973,1,0.972477,0.972973]
kappa
0.9723204328538309
kappa
0.9822064933283144
kappa
0.990114370749795
kappa
0.9822060551478607
kappa
0.9901144403049396
kappa
0.9742966405505149
kappa
0.9822061803444783
kappa
0.9683673218111397
kappa
0.976274656731855
kappa
0.9802290892716424
kb_relative_information_score
0.9764897266836651
kb_relative_information_score
0.9832300555522261
kb_relative_information_score
0.9914335490945005
kb_relative_information_score
0.9836579303540308
kb_relative_information_score
0.9874897757202001
kb_relative_information_score
0.975296464823109
kb_relative_information_score
0.9794361631371544
kb_relative_information_score
0.9697988658755545
kb_relative_information_score
0.9801858026637145
kb_relative_information_score
0.9819603594874943
mean_absolute_error
0.005965763182803916
mean_absolute_error
0.0041414725895465
mean_absolute_error
0.0020977797606620188
mean_absolute_error
0.0036965554494070604
mean_absolute_error
0.003027003528139865
mean_absolute_error
0.005581878936731775
mean_absolute_error
0.005339833246495905
mean_absolute_error
0.007296397136476653
mean_absolute_error
0.004932094469284487
mean_absolute_error
0.004097210010585783
mean_prior_absolute_error
0.17999677629374952
mean_prior_absolute_error
0.17999677629374952
mean_prior_absolute_error
0.17999715555330845
mean_prior_absolute_error
0.17999715555330845
mean_prior_absolute_error
0.1799969027136025
mean_prior_absolute_error
0.1799969027136025
mean_prior_absolute_error
0.17999759802279386
mean_prior_absolute_error
0.17999759802279386
mean_prior_absolute_error
0.1799979140724263
mean_prior_absolute_error
0.17999879901139712
number_of_instances
562 [55,57,56,58,57,56,56,56,55,56]
number_of_instances
562 [55,57,56,58,57,56,56,56,55,56]
number_of_instances
562 [55,57,56,57,57,56,56,57,55,56]
number_of_instances
562 [55,57,56,57,57,56,56,57,55,56]
number_of_instances
562 [55,57,56,57,57,55,56,57,55,57]
number_of_instances
562 [55,57,56,57,57,55,56,57,55,57]
number_of_instances
562 [56,57,55,57,57,56,55,57,56,56]
number_of_instances
562 [56,57,55,57,57,56,55,57,56,56]
number_of_instances
562 [56,58,55,57,56,56,56,56,56,56]
number_of_instances
562 [56,57,56,57,56,56,56,56,56,56]
precision
0.9755024518206633 [1,0.95,0.964912,1,0.981818,1,0.948276,0.964912,0.981481,0.963636]
precision
0.9847015993782469 [1,1,1,1,0.982456,0.965517,1,1,0.981818,0.916667]
precision
0.9913701067615658 [1,1,1,0.982456,0.982456,1,1,0.95,1,1]
precision
0.9840708831055561 [1,0.965517,1,1,0.982759,0.982456,0.982456,0.982759,0.982143,0.962963]
precision
0.9911974300089407 [1,0.982759,1,1,1,0.964286,1,1,0.982143,0.982143]
precision
0.9778086441794301 [1,0.966102,1,1,0.965517,0.980769,1,1,0.963636,0.903226]
precision
0.9844163613414442 [1,1,0.982143,1,0.982759,0.965517,1,0.982456,1,0.931034]
precision
0.9721379476670948 [0.982456,0.981818,0.982143,1,0.982143,0.947368,1,0.948276,0.949153,0.948276]
precision
0.9788886338046389 [0.982456,0.982759,0.981818,0.965517,1,1,1,0.981818,0.963636,0.931034]
precision
0.9825625369048521 [0.982143,0.95,0.982456,1,0.982143,0.965517,0.981818,1,1,0.981818]
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9911032028469751
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9911032028469751
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.9786476868327402
predictive_accuracy
0.9822064056939501
prior_entropy
3.3217909017967746
prior_entropy
3.3217909017967746
prior_entropy
3.321817923867619
prior_entropy
3.321817923867619
prior_entropy
3.3217996202390836
prior_entropy
3.3217996202390836
prior_entropy
3.3218501976437715
prior_entropy
3.3218501976437715
prior_entropy
3.321873176216062
prior_entropy
3.3219367883600994
relative_absolute_error
0.03314372238016065
relative_absolute_error
0.0230085931249554
relative_absolute_error
0.01165451617395551
relative_absolute_error
0.020536743694887324
relative_absolute_error
0.01681697563960978
relative_absolute_error
0.03101097214774434
relative_absolute_error
0.02966613613265939
relative_absolute_error
0.04053608057343454
relative_absolute_error
0.027400842363650642
relative_absolute_error
0.022762429711135776
root_mean_prior_squared_error
0.2999968250410308
root_mean_prior_squared_error
0.2999968250410308
root_mean_prior_squared_error
0.2999974571463194
root_mean_prior_squared_error
0.2999974571463194
root_mean_prior_squared_error
0.2999970357429417
root_mean_prior_squared_error
0.2999970357429417
root_mean_prior_squared_error
0.2999981946008062
root_mean_prior_squared_error
0.2999981946008062
root_mean_prior_squared_error
0.2999987213529011
root_mean_prior_squared_error
0.3000001962538465
root_mean_squared_error
0.05926101301485864
root_mean_squared_error
0.05132992531480173
root_mean_squared_error
0.0375853595006103
root_mean_squared_error
0.05205285169245102
root_mean_squared_error
0.04226792859572453
root_mean_squared_error
0.06452025074477667
root_mean_squared_error
0.051153596630925974
root_mean_squared_error
0.06715592059247726
root_mean_squared_error
0.05642881787524177
root_mean_squared_error
0.05376321365275988
root_relative_squared_error
0.19753880064148505
root_relative_squared_error
0.17110156185080058
root_relative_squared_error
0.12528559361181046
root_relative_squared_error
0.17351097635158616
root_relative_squared_error
0.14089448747734504
root_relative_squared_error
0.21506962755479397
root_relative_squared_error
0.17051301491661883
root_relative_squared_error
0.22385441579686358
root_relative_squared_error
0.1880968612824925
root_relative_squared_error
0.17921059493997096
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
unweighted_recall
0.9751197350743629 [0.981818,1,0.982143,0.965517,0.947368,1,0.982143,0.982143,0.963636,0.946429]
unweighted_recall
0.984205065956427 [1,0.982456,1,0.931034,0.982456,1,1,0.982143,0.981818,0.982143]
unweighted_recall
0.9911340852130325 [1,1,1,0.982456,0.982456,1,1,1,1,0.946429]
unweighted_recall
0.9840225563909775 [1,0.982456,0.964286,0.964912,1,1,1,1,1,0.928571]
unweighted_recall
0.9910691501480976 [0.981818,1,1,1,1,0.981818,0.982143,1,1,0.964912]
unweighted_recall
0.9767150831624514 [0.981818,1,1,0.964912,0.982456,0.927273,0.982143,0.982456,0.963636,0.982456]
unweighted_recall
0.9840214171793118 [0.982143,0.964912,1,0.982456,1,1,0.981818,0.982456,0.982143,0.964286]
unweighted_recall
0.9718358395989976 [1,0.947368,1,0.894737,0.964912,0.964286,1,0.964912,1,0.982143]
unweighted_recall
0.9786318657144427 [1,0.982759,0.981818,0.982456,0.982143,0.982143,1,0.964286,0.946429,0.964286]
unweighted_recall
0.982174185463659 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.946429,0.964286]
usercpu_time_millis
4586.897351999141
usercpu_time_millis
7715.527594000378
usercpu_time_millis
11241.617841000334
usercpu_time_millis
9771.324120998543
usercpu_time_millis
7489.614092999545
usercpu_time_millis
11210.73884100042
usercpu_time_millis
4275.331353999718
usercpu_time_millis
5343.5958639984165
usercpu_time_millis
6833.133182000893
usercpu_time_millis
8716.018107998025
usercpu_time_millis_testing
4.263900998921599
usercpu_time_millis_testing
6.45280000026105
usercpu_time_millis_testing
6.974699999773293
usercpu_time_millis_testing
6.234799999219831
usercpu_time_millis_testing
6.308899999567075
usercpu_time_millis_testing
6.88350000018545
usercpu_time_millis_testing
5.2015000001119915
usercpu_time_millis_testing
5.74869999945804
usercpu_time_millis_testing
5.258699000478373
usercpu_time_millis_testing
5.771999998614774
usercpu_time_millis_training
4582.63345100022
usercpu_time_millis_training
7709.0747940001165
usercpu_time_millis_training
11234.64314100056
usercpu_time_millis_training
9765.089320999323
usercpu_time_millis_training
7483.305192999978
usercpu_time_millis_training
11203.855341000235
usercpu_time_millis_training
4270.129853999606
usercpu_time_millis_training
5337.847163998958
usercpu_time_millis_training
6827.874483000414
usercpu_time_millis_training
8710.24610799941
wall_clock_time_millis
4593.696355819702
wall_clock_time_millis
7717.852830886841
wall_clock_time_millis
11248.443603515625
wall_clock_time_millis
9772.43685722351
wall_clock_time_millis
7492.202997207642
wall_clock_time_millis
11216.73035621643
wall_clock_time_millis
4280.600070953369
wall_clock_time_millis
5368.893146514893
wall_clock_time_millis
6841.678619384766
wall_clock_time_millis
8730.984926223755
wall_clock_time_millis_testing
4.266023635864258
wall_clock_time_millis_testing
6.4563751220703125
wall_clock_time_millis_testing
6.97779655456543
wall_clock_time_millis_testing
6.238222122192383
wall_clock_time_millis_testing
6.322622299194336
wall_clock_time_millis_testing
6.885051727294922
wall_clock_time_millis_testing
5.207538604736328
wall_clock_time_millis_testing
5.752801895141602
wall_clock_time_millis_testing
5.265712738037109
wall_clock_time_millis_testing
5.775213241577148
wall_clock_time_millis_training
4589.430332183838
wall_clock_time_millis_training
7711.3964557647705
wall_clock_time_millis_training
11241.46580696106
wall_clock_time_millis_training
9766.198635101318
wall_clock_time_millis_training
7485.880374908447
wall_clock_time_millis_training
11209.845304489136
wall_clock_time_millis_training
4275.392532348633
wall_clock_time_millis_training
5363.140344619751
wall_clock_time_millis_training
6836.4129066467285
wall_clock_time_millis_training
8725.209712982178
weighted_recall
0.9750889679715302 [0.981818,1,0.982143,0.965517,0.947368,1,0.982143,0.982143,0.963636,0.946429]
weighted_recall
0.9839857651245552 [1,0.982456,1,0.931034,0.982456,1,1,0.982143,0.981818,0.982143]
weighted_recall
0.9911032028469751 [1,1,1,0.982456,0.982456,1,1,1,1,0.946429]
weighted_recall
0.9839857651245552 [1,0.982456,0.964286,0.964912,1,1,1,1,1,0.928571]
weighted_recall
0.9911032028469751 [0.981818,1,1,1,1,0.981818,0.982143,1,1,0.964912]
weighted_recall
0.9768683274021353 [0.981818,1,1,0.964912,0.982456,0.927273,0.982143,0.982456,0.963636,0.982456]
weighted_recall
0.9839857651245552 [0.982143,0.964912,1,0.982456,1,1,0.981818,0.982456,0.982143,0.964286]
weighted_recall
0.9715302491103203 [1,0.947368,1,0.894737,0.964912,0.964286,1,0.964912,1,0.982143]
weighted_recall
0.9786476868327402 [1,0.982759,0.981818,0.982456,0.982143,0.982143,1,0.964286,0.946429,0.964286]
weighted_recall
0.9822064056939501 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.946429,0.964286]