10578828
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)
8295110
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
"most_frequent"
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
0.1398256092300441
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
406
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
95
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
7
19038
random_state
44857
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.30514739720467254
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
22083923
description
https://api.openml.org/data/download/22083923/description.xml
-1
22083925
predictions
https://api.openml.org/data/download/22083925/predictions.arff
area_under_roc_curve
0.9995397058640785 [0.999936,0.999663,0.999918,0.999568,0.999792,0.999195,0.999644,0.999828,0.999347,0.998503]
average_cost
0
f_measure
0.9754865929371763 [0.990958,0.969749,0.990991,0.974494,0.981498,0.978339,0.984698,0.976211,0.964896,0.943363]
kappa
0.9727159579456506
kb_relative_information_score
0.9737280276590811
mean_absolute_error
0.006749329082896463
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9754448398576513 [0.98917,0.982487,0.987433,0.968531,0.980634,0.971326,0.980287,0.978799,0.967509,0.948399]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.975594504708869 [0.992754,0.957338,0.994575,0.980531,0.982363,0.985455,0.98915,0.973638,0.962298,0.93838]
predictive_accuracy
0.9754448398576513
prior_entropy
3.3218327251668773
relative_absolute_error
0.03749682308923485
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.06001867549306802
root_relative_squared_error
0.20006372259967864
total_cost
0
unweighted_recall
0.9754573578213824 [0.98917,0.982487,0.987433,0.968531,0.980634,0.971326,0.980287,0.978799,0.967509,0.948399]
area_under_roc_curve
0.9995532689726595 [1,0.999583,0.999965,0.999932,0.999201,1,0.999012,0.999824,0.999283,0.99873]
area_under_roc_curve
0.9998310528786869 [1,1,1,0.999384,0.999931,0.999859,1,1,0.999426,0.999718]
area_under_roc_curve
0.9997467476528554 [1,1,0.999929,0.999444,1,1,1,1,0.999749,0.998341]
area_under_roc_curve
0.9994826465645831 [1,0.999409,0.999718,0.998506,1,0.999965,1,0.999792,0.999821,0.997636]
area_under_roc_curve
0.9997047504378178 [0.999785,0.999826,1,1,1,0.999068,0.999153,1,0.999713,0.999479]
area_under_roc_curve
0.9990648383719539 [0.999964,0.999618,0.999894,0.999826,0.999618,0.996629,0.999541,0.999618,0.998315,0.997568]
area_under_roc_curve
0.9997642953564815 [0.999612,0.999792,1,0.999653,0.999931,0.999859,0.999641,0.999792,1,0.999365]
area_under_roc_curve
0.9996690780017193 [1,0.999583,1,0.999375,0.999896,0.999682,1,0.999305,0.999612,0.999259]
area_under_roc_curve
0.9991169344729297 [1,0.999008,0.999677,0.999618,1,0.998341,1,0.999929,0.998271,0.99633]
area_under_roc_curve
0.9997924974301545 [0.999824,0.999861,1,1,0.999753,0.999965,0.999541,1,0.999647,0.999329]
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
0.9644291920243431 [0.990826,0.964912,0.982143,0.974359,0.955752,0.990991,0.955752,0.973451,0.929825,0.925926]
f_measure
0.9822040550205084 [1,0.982143,0.99115,0.964912,0.982759,0.982143,0.990991,0.981818,0.972973,0.973913]
f_measure
0.9839340309063183 [0.990826,0.982759,0.990991,0.964912,0.99115,1,1,0.982759,0.990991,0.945455]
f_measure
0.973400211077914 [1,0.965517,0.981818,0.964286,1,0.990991,0.99115,0.956522,0.981818,0.902655]
f_measure
0.9838996000111957 [0.990826,0.974359,1,1,0.991304,0.981818,0.972477,0.991304,0.982143,0.954955]
f_measure
0.9645518514763445 [0.990826,0.957983,0.990991,0.964286,0.964912,0.933333,0.990991,0.982456,0.945455,0.92437]
f_measure
0.9768949388085576 [0.982143,0.964912,0.990991,0.964286,0.99115,0.973913,0.981481,0.965517,0.990991,0.964286]
f_measure
0.9715549982069328 [0.99115,0.964912,1,0.982143,0.973451,0.964286,0.990991,0.938053,0.963636,0.948276]
f_measure
0.9752076735747801 [0.99115,0.974359,0.990826,0.973913,0.990991,0.972477,1,0.990991,0.928571,0.93913]
f_measure
0.9786548222262116 [0.982143,0.966102,0.990991,0.991304,0.973451,0.990991,0.972973,1,0.963636,0.954955]
kappa
0.9604579003285794
kappa
0.9802291588245847
kappa
0.9822058673496311
kappa
0.9703433209148189
kappa
0.9822058673496311
kappa
0.9604556744699865
kappa
0.9742976352135766
kappa
0.9683668766864023
kappa
0.9723201407211961
kappa
0.976274656731855
kb_relative_information_score
0.9655836969730186
kb_relative_information_score
0.9806154588263274
kb_relative_information_score
0.9818207058116202
kb_relative_information_score
0.9727338318309506
kb_relative_information_score
0.9801796552522646
kb_relative_information_score
0.9633145478077594
kb_relative_information_score
0.9733532397854708
kb_relative_information_score
0.9715050696369597
kb_relative_information_score
0.9721408109350057
kb_relative_information_score
0.9760331968295851
mean_absolute_error
0.008211806885738835
mean_absolute_error
0.005500179963021083
mean_absolute_error
0.005412099836964022
mean_absolute_error
0.006987271499356426
mean_absolute_error
0.004989986795495081
mean_absolute_error
0.009152391577678921
mean_absolute_error
0.006993515356130328
mean_absolute_error
0.007368188621272235
mean_absolute_error
0.006758727801936489
mean_absolute_error
0.006119122491371277
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
0.9650157238875211 [1,0.964912,0.982143,0.966102,0.964286,1,0.947368,0.964912,0.898305,0.961538]
precision
0.9826296847734874 [1,1,0.982456,0.982143,0.966102,0.982143,1,1,0.964286,0.949153]
precision
0.9841270040731707 [1,0.966102,1,0.964912,1,1,1,0.966102,0.982143,0.962963]
precision
0.9737364100255613 [1,0.949153,1,0.981818,1,1,0.982456,0.948276,0.981818,0.894737]
precision
0.9843400402876541 [1,0.95,1,1,0.982759,0.981818,1,0.982759,0.964912,0.981481]
precision
0.9658921322048402 [1,0.919355,1,0.981818,0.964912,0.98,1,0.982456,0.945455,0.887097]
precision
0.9772877772146427 [0.982143,0.964912,0.982143,0.981818,1,0.949153,1,0.949153,1,0.964286]
precision
0.9719933607248646 [0.982456,0.964912,1,1,0.982143,0.964286,0.982143,0.946429,0.981481,0.916667]
precision
0.9756942388104808 [0.982456,0.966102,1,0.965517,1,1,1,1,0.928571,0.915254]
precision
0.9790445581654686 [0.982143,0.934426,1,0.982759,0.964912,1,0.981818,1,0.981481,0.963636]
predictive_accuracy
0.9644128113879004
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9644128113879004
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9786476868327402
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
0.045621966430873205
relative_absolute_error
0.030557102611909834
relative_absolute_error
0.030067696460687455
relative_absolute_error
0.038818788429615246
relative_absolute_error
0.027722625891150873
relative_absolute_error
0.05084749481629424
relative_absolute_error
0.03885338156148455
relative_absolute_error
0.040934927477972075
relative_absolute_error
0.037548922923723214
relative_absolute_error
0.03399535177445172
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
0.07038549652797087
root_mean_squared_error
0.05123540840838306
root_mean_squared_error
0.046903487388784575
root_mean_squared_error
0.06053457055871988
root_mean_squared_error
0.05344606412974509
root_mean_squared_error
0.07371436234095911
root_mean_squared_error
0.05881629724887724
root_mean_squared_error
0.06149669458412103
root_mean_squared_error
0.06305671863060004
root_mean_squared_error
0.0554185754382588
root_relative_squared_error
0.23462080479799804
root_relative_squared_error
0.17078650216173305
root_relative_squared_error
0.15634628318168736
root_relative_squared_error
0.20178361221640295
root_relative_squared_error
0.17815530742624205
root_relative_squared_error
0.24571696903072973
root_relative_squared_error
0.1960555040244205
root_relative_squared_error
0.20499021557763655
root_relative_squared_error
0.2101899579646
root_relative_squared_error
0.18472846394862402
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
0.9644065296470015 [0.981818,0.964912,0.982143,0.982759,0.947368,0.982143,0.964286,0.982143,0.963636,0.892857]
unweighted_recall
0.9823577753160329 [1,0.964912,1,0.948276,1,0.982143,0.982143,0.964286,0.981818,1]
unweighted_recall
0.9839900888585099 [0.981818,1,0.982143,0.964912,0.982456,1,1,1,1,0.928571]
unweighted_recall
0.9733697881066302 [1,0.982456,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.910714]
unweighted_recall
0.9839889496468442 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.929825]
unweighted_recall
0.9642116655274551 [0.981818,1,0.982143,0.947368,0.964912,0.890909,0.982143,0.982456,0.945455,0.964912]
unweighted_recall
0.9769400774663932 [0.982143,0.964912,1,0.947368,0.982456,1,0.963636,0.982456,0.982143,0.964286]
unweighted_recall
0.9717418546365915 [1,0.964912,1,0.964912,0.964912,0.964286,1,0.929825,0.946429,0.982143]
unweighted_recall
0.975060437143014 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.928571,0.964286]
unweighted_recall
0.9785714285714284 [0.982143,1,0.982143,1,0.982143,0.982143,0.964286,1,0.946429,0.946429]
usercpu_time_millis
10843.681037000351
usercpu_time_millis
11393.03854299942
usercpu_time_millis
11283.851340000183
usercpu_time_millis
12120.541254000273
usercpu_time_millis
12127.595354997538
usercpu_time_millis
12123.27744400136
usercpu_time_millis
10392.926326001543
usercpu_time_millis
10466.88653199999
usercpu_time_millis
10146.345024999391
usercpu_time_millis
10029.146426000807
usercpu_time_millis_testing
7.997900000191294
usercpu_time_millis_testing
7.813698999598273
usercpu_time_millis_testing
7.798200000252109
usercpu_time_millis_testing
9.188800000629271
usercpu_time_millis_testing
8.167700998455985
usercpu_time_millis_testing
8.005000001503504
usercpu_time_millis_testing
8.617700001195772
usercpu_time_millis_testing
7.793900000251597
usercpu_time_millis_testing
8.776599999691825
usercpu_time_millis_testing
8.123300000079325
usercpu_time_millis_training
10835.68313700016
usercpu_time_millis_training
11385.224843999822
usercpu_time_millis_training
11276.05313999993
usercpu_time_millis_training
12111.352453999643
usercpu_time_millis_training
12119.427653999082
usercpu_time_millis_training
12115.272443999856
usercpu_time_millis_training
10384.308626000347
usercpu_time_millis_training
10459.092631999738
usercpu_time_millis_training
10137.5684249997
usercpu_time_millis_training
10021.023126000728
wall_clock_time_millis
10845.544576644897
wall_clock_time_millis
11398.690938949585
wall_clock_time_millis
11295.344114303589
wall_clock_time_millis
12155.980110168457
wall_clock_time_millis
12130.40280342102
wall_clock_time_millis
12157.969951629639
wall_clock_time_millis
10408.38623046875
wall_clock_time_millis
10482.63931274414
wall_clock_time_millis
10167.82546043396
wall_clock_time_millis
10033.916473388672
wall_clock_time_millis_testing
8.002519607543945
wall_clock_time_millis_testing
7.816791534423828
wall_clock_time_millis_testing
7.802009582519531
wall_clock_time_millis_testing
9.195089340209961
wall_clock_time_millis_testing
8.170366287231445
wall_clock_time_millis_testing
8.008241653442383
wall_clock_time_millis_testing
8.622169494628906
wall_clock_time_millis_testing
7.799386978149414
wall_clock_time_millis_testing
8.781194686889648
wall_clock_time_millis_testing
8.130073547363281
wall_clock_time_millis_training
10837.542057037354
wall_clock_time_millis_training
11390.874147415161
wall_clock_time_millis_training
11287.54210472107
wall_clock_time_millis_training
12146.785020828247
wall_clock_time_millis_training
12122.232437133789
wall_clock_time_millis_training
12149.961709976196
wall_clock_time_millis_training
10399.764060974121
wall_clock_time_millis_training
10474.839925765991
wall_clock_time_millis_training
10159.04426574707
wall_clock_time_millis_training
10025.786399841309
weighted_recall
0.9644128113879004 [0.981818,0.964912,0.982143,0.982759,0.947368,0.982143,0.964286,0.982143,0.963636,0.892857]
weighted_recall
0.9822064056939501 [1,0.964912,1,0.948276,1,0.982143,0.982143,0.964286,0.981818,1]
weighted_recall
0.9839857651245552 [0.981818,1,0.982143,0.964912,0.982456,1,1,1,1,0.928571]
weighted_recall
0.9733096085409253 [1,0.982456,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.910714]
weighted_recall
0.9839857651245552 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.929825]
weighted_recall
0.9644128113879004 [0.981818,1,0.982143,0.947368,0.964912,0.890909,0.982143,0.982456,0.945455,0.964912]
weighted_recall
0.9768683274021353 [0.982143,0.964912,1,0.947368,0.982456,1,0.963636,0.982456,0.982143,0.964286]
weighted_recall
0.9715302491103203 [1,0.964912,1,0.964912,0.964912,0.964286,1,0.929825,0.946429,0.982143]
weighted_recall
0.9750889679715302 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.928571,0.964286]
weighted_recall
0.9786476868327402 [0.982143,1,0.982143,1,0.982143,0.982143,0.964286,1,0.946429,0.946429]