10578607
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)
8294889
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
0.11897476448102996
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1084
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
171
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
14847
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.3799599358839793
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
22083481
description
https://api.openml.org/data/download/22083481/description.xml
-1
22083482
predictions
https://api.openml.org/data/download/22083482/predictions.arff
area_under_roc_curve
0.9995071626454518 [0.999967,0.999659,0.999837,0.999643,0.999657,0.998919,0.999817,0.999812,0.999415,0.998343]
average_cost
0
f_measure
0.9781656269592097 [0.991855,0.975652,0.991928,0.974449,0.977935,0.981098,0.987455,0.98227,0.971014,0.948381]
kappa
0.9756817139301185
kb_relative_information_score
0.973192282952486
mean_absolute_error
0.00737341181926346
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9781138790035587 [0.98917,0.982487,0.992819,0.966783,0.975352,0.976703,0.987455,0.978799,0.967509,0.964413]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9783038012747056 [0.994555,0.968912,0.991039,0.982238,0.980531,0.985533,0.987455,0.985765,0.974545,0.932874]
predictive_accuracy
0.9781138790035587
prior_entropy
3.3218327251668773
relative_absolute_error
0.040964000296210855
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.059089481704310796
root_relative_squared_error
0.19696638719752138
total_cost
0
unweighted_recall
0.9781488670476893 [0.98917,0.982487,0.992819,0.966783,0.975352,0.976703,0.987455,0.978799,0.967509,0.964413]
area_under_roc_curve
0.9993629866593643 [1,0.999722,0.999929,0.999487,0.998159,1,0.999824,0.999788,0.999426,0.997318]
area_under_roc_curve
0.9996692441596214 [1,0.999826,1,0.999487,0.999514,0.999612,1,0.999894,0.999283,0.999082]
area_under_roc_curve
0.9997396312430252 [1,1,1,0.999583,0.999722,1,1,0.999965,1,0.99813]
area_under_roc_curve
0.9996340240727501 [1,0.999792,0.999435,0.998888,1,1,1,0.999861,0.999821,0.998553]
area_under_roc_curve
0.9997501594751403 [0.999857,0.999514,1,1,1,0.999821,0.999471,1,0.999749,0.999097]
area_under_roc_curve
0.9989351018421824 [0.999964,0.999757,1,0.999687,0.999375,0.995804,0.999541,0.999861,0.997454,0.997811]
area_under_roc_curve
0.9998311719737473 [0.999894,0.999757,1,0.999965,0.999965,0.999824,0.999713,0.999861,0.999859,0.999471]
area_under_roc_curve
0.9995320728835152 [0.999965,0.999792,0.999928,0.999757,0.999722,0.9994,0.999964,0.999479,1,0.997318]
area_under_roc_curve
0.9989447083319445 [1,0.999111,0.999319,0.999479,1,0.9964,1,0.999612,0.998518,0.997]
area_under_roc_curve
0.9998593113218175 [0.999929,0.999931,1,0.999931,1,0.999929,0.999612,1,0.999788,0.999471]
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
0.9769145582688661 [1,0.973913,0.982143,0.982456,0.973451,1,0.973451,0.973451,0.946429,0.963636]
f_measure
0.9752164042056777 [0.990826,0.964912,1,0.964286,0.964912,0.973451,1,0.981818,0.963636,0.949153]
f_measure
0.9892555648454789 [1,1,1,0.973913,0.973913,1,1,0.991304,1,0.954128]
f_measure
0.9840299107497206 [1,0.973913,0.981818,0.972973,1,1,0.99115,0.99115,0.982143,0.947368]
f_measure
0.9840437527881644 [0.981481,0.974359,1,1,0.99115,0.981818,0.981818,1,0.972973,0.956522]
f_measure
0.968013459116211 [0.981818,0.982759,1,0.964912,0.948276,0.952381,0.982143,0.982143,0.944444,0.941176]
f_measure
0.9769742815467869 [0.990991,0.964286,0.990991,0.982143,0.982456,0.973451,0.981818,0.973913,0.990991,0.93913]
f_measure
0.9751567344117654 [0.99115,0.982143,0.990991,0.973451,0.964286,0.982143,0.990991,0.946429,0.990991,0.940171]
f_measure
0.9715843403535629 [1,0.966102,0.981818,0.956522,0.990991,0.963636,1,0.982143,0.945455,0.929825]
f_measure
0.9804210451491027 [0.982143,0.974359,0.99115,0.973913,0.990991,0.982143,0.972973,1,0.972477,0.964286]
kappa
0.9742979968901491
kappa
0.9723210171006019
kappa
0.9881372448997541
kappa
0.9822063681361012
kappa
0.9822056795474374
kappa
0.9644101070229878
kappa
0.9742979968901491
kappa
0.9723214065847472
kappa
0.9683657638197496
kappa
0.9782518451807186
kb_relative_information_score
0.9707340170275129
kb_relative_information_score
0.9747661391584589
kb_relative_information_score
0.9793054644852794
kb_relative_information_score
0.9748903011783027
kb_relative_information_score
0.9771264302198058
kb_relative_information_score
0.9609036477638849
kb_relative_information_score
0.9757043730306587
kb_relative_information_score
0.9713748080806233
kb_relative_information_score
0.967665572596814
kb_relative_information_score
0.979451883945233
mean_absolute_error
0.007916822886361762
mean_absolute_error
0.006974273358771771
mean_absolute_error
0.0062097115698388035
mean_absolute_error
0.0073343256128146055
mean_absolute_error
0.00636930852514602
mean_absolute_error
0.0102301097233971
mean_absolute_error
0.006624089768500827
mean_absolute_error
0.007571990971010991
mean_absolute_error
0.00849683437674664
mean_absolute_error
0.006006651400046211
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
0.9772066101325908 [1,0.965517,0.982143,1,0.982143,1,0.964912,0.964912,0.929825,0.981481]
precision
0.9761845780793391 [1,0.964912,1,1,0.964912,0.964912,1,1,0.963636,0.903226]
precision
0.9893765180123965 [1,1,1,0.965517,0.965517,1,1,0.982759,1,0.981132]
precision
0.9844486353938595 [1,0.965517,1,1,1,1,0.982456,1,0.964912,0.931034]
precision
0.9844082534228563 [1,0.95,1,1,1,0.981818,1,1,0.964286,0.948276]
precision
0.9690601229539808 [0.981818,0.966102,1,0.964912,0.932203,1,0.982143,1,0.962264,0.903226]
precision
0.9774115681006192 [1,0.981818,0.982143,1,0.982456,0.964912,0.981818,0.965517,1,0.915254]
precision
0.9758329419432453 [0.982456,1,0.982143,0.982143,0.981818,0.982143,0.982143,0.963636,1,0.901639]
precision
0.9719093003913227 [1,0.95,0.981818,0.948276,1,0.981481,1,0.982143,0.962963,0.913793]
precision
0.9807541722421496 [0.982143,0.95,0.982456,0.965517,1,0.982143,0.981818,1,1,0.964286]
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.98932384341637
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9679715302491103
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.9804270462633453
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
0.04398313708375386
relative_absolute_error
0.038746657036734695
relative_absolute_error
0.03449894277912474
relative_absolute_error
0.04074689730662134
relative_absolute_error
0.0353856562480988
relative_absolute_error
0.05683492087458016
relative_absolute_error
0.03680098979799714
relative_absolute_error
0.042067177863407475
relative_absolute_error
0.0472051824629909
relative_absolute_error
0.033370508209145784
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
0.062270424652328814
root_mean_squared_error
0.057056722985041275
root_mean_squared_error
0.04899739375616958
root_mean_squared_error
0.055486928585786806
root_mean_squared_error
0.05326323262544569
root_mean_squared_error
0.07337127675918106
root_mean_squared_error
0.05518858628865251
root_mean_squared_error
0.06234926403148143
root_mean_squared_error
0.0669274132361879
root_mean_squared_error
0.0516743997604891
root_relative_squared_error
0.20757027893149213
root_relative_squared_error
0.1901910894464886
root_relative_squared_error
0.16332603023455566
root_relative_squared_error
0.184957996356362
root_relative_squared_error
0.17754586305674475
root_relative_squared_error
0.24457333912475945
root_relative_squared_error
0.18396306138471744
root_relative_squared_error
0.207832130838143
root_relative_squared_error
0.22309232830848758
root_relative_squared_error
0.17224788652059608
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
0.9769379168925447 [1,0.982456,0.982143,0.965517,0.964912,1,0.982143,0.982143,0.963636,0.946429]
unweighted_recall
0.9752742161045246 [0.981818,0.964912,1,0.931034,0.964912,0.982143,1,0.964286,0.963636,1]
unweighted_recall
0.9893483709273182 [1,1,1,0.982456,0.982456,1,1,1,1,0.928571]
unweighted_recall
0.9840852130325815 [1,0.982456,0.964286,0.947368,1,1,1,0.982456,1,0.964286]
unweighted_recall
0.9838926862611075 [0.963636,1,1,1,0.982456,0.981818,0.964286,1,0.981818,0.964912]
unweighted_recall
0.9677517657780814 [0.981818,1,1,0.964912,0.964912,0.909091,0.982143,0.964912,0.927273,0.982456]
unweighted_recall
0.9769725449988605 [0.982143,0.947368,1,0.964912,0.982456,0.982143,0.981818,0.982456,0.982143,0.964286]
unweighted_recall
0.975344611528822 [1,0.964912,1,0.964912,0.947368,0.982143,1,0.929825,0.982143,0.982143]
unweighted_recall
0.9715203368923875 [1,0.982759,0.981818,0.964912,0.982143,0.946429,1,0.982143,0.928571,0.946429]
unweighted_recall
0.9803884711779448 [0.982143,1,1,0.982456,0.982143,0.982143,0.964286,1,0.946429,0.964286]
usercpu_time_millis
10477.857427002164
usercpu_time_millis
10516.722329000913
usercpu_time_millis
10481.325028000356
usercpu_time_millis
10479.715528999805
usercpu_time_millis
10538.86802299894
usercpu_time_millis
10512.797927000065
usercpu_time_millis
10530.758231998334
usercpu_time_millis
10573.321632000443
usercpu_time_millis
10610.89414000162
usercpu_time_millis
10449.153931000183
usercpu_time_millis_testing
10.279300000547664
usercpu_time_millis_testing
10.562400000708294
usercpu_time_millis_testing
9.375999999974738
usercpu_time_millis_testing
10.099899998749606
usercpu_time_millis_testing
8.925699999963399
usercpu_time_millis_testing
9.986799999751383
usercpu_time_millis_testing
9.546299999783514
usercpu_time_millis_testing
8.431701000517933
usercpu_time_millis_testing
8.333700001458055
usercpu_time_millis_testing
10.094600000229548
usercpu_time_millis_training
10467.578127001616
usercpu_time_millis_training
10506.159929000205
usercpu_time_millis_training
10471.949028000381
usercpu_time_millis_training
10469.615629001055
usercpu_time_millis_training
10529.942322998977
usercpu_time_millis_training
10502.811127000314
usercpu_time_millis_training
10521.21193199855
usercpu_time_millis_training
10564.889930999925
usercpu_time_millis_training
10602.560440000161
usercpu_time_millis_training
10439.059330999953
wall_clock_time_millis
10490.641117095947
wall_clock_time_millis
10524.450778961182
wall_clock_time_millis
10487.125873565674
wall_clock_time_millis
10480.29375076294
wall_clock_time_millis
10568.016052246094
wall_clock_time_millis
10527.4977684021
wall_clock_time_millis
10541.889190673828
wall_clock_time_millis
10581.63046836853
wall_clock_time_millis
10668.228387832642
wall_clock_time_millis
10473.692655563354
wall_clock_time_millis_testing
10.28585433959961
wall_clock_time_millis_testing
10.569334030151367
wall_clock_time_millis_testing
9.382486343383789
wall_clock_time_millis_testing
10.104894638061523
wall_clock_time_millis_testing
8.927345275878906
wall_clock_time_millis_testing
9.991168975830078
wall_clock_time_millis_testing
9.549140930175781
wall_clock_time_millis_testing
8.436203002929688
wall_clock_time_millis_testing
8.336544036865234
wall_clock_time_millis_testing
10.099411010742188
wall_clock_time_millis_training
10480.355262756348
wall_clock_time_millis_training
10513.88144493103
wall_clock_time_millis_training
10477.74338722229
wall_clock_time_millis_training
10470.188856124878
wall_clock_time_millis_training
10559.088706970215
wall_clock_time_millis_training
10517.50659942627
wall_clock_time_millis_training
10532.340049743652
wall_clock_time_millis_training
10573.1942653656
wall_clock_time_millis_training
10659.891843795776
wall_clock_time_millis_training
10463.593244552612
weighted_recall
0.9768683274021353 [1,0.982456,0.982143,0.965517,0.964912,1,0.982143,0.982143,0.963636,0.946429]
weighted_recall
0.9750889679715302 [0.981818,0.964912,1,0.931034,0.964912,0.982143,1,0.964286,0.963636,1]
weighted_recall
0.9893238434163701 [1,1,1,0.982456,0.982456,1,1,1,1,0.928571]
weighted_recall
0.9839857651245552 [1,0.982456,0.964286,0.947368,1,1,1,0.982456,1,0.964286]
weighted_recall
0.9839857651245552 [0.963636,1,1,1,0.982456,0.981818,0.964286,1,0.981818,0.964912]
weighted_recall
0.9679715302491103 [0.981818,1,1,0.964912,0.964912,0.909091,0.982143,0.964912,0.927273,0.982456]
weighted_recall
0.9768683274021353 [0.982143,0.947368,1,0.964912,0.982456,0.982143,0.981818,0.982456,0.982143,0.964286]
weighted_recall
0.9750889679715302 [1,0.964912,1,0.964912,0.947368,0.982143,1,0.929825,0.982143,0.982143]
weighted_recall
0.9715302491103203 [1,0.982759,0.981818,0.964912,0.982143,0.946429,1,0.982143,0.928571,0.946429]
weighted_recall
0.9804270462633452 [0.982143,1,1,0.982456,0.982143,0.982143,0.964286,1,0.946429,0.964286]