10578647
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)
8294929
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
"median"
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
0.9344891939550843
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
146
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
97
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
5
19038
random_state
17155
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.15632138164538553
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
22083561
description
https://api.openml.org/data/download/22083561/description.xml
-1
22083562
predictions
https://api.openml.org/data/download/22083562/predictions.arff
area_under_roc_curve
0.9992246436791805 [0.999651,0.999601,0.999783,0.999232,0.999441,0.998986,0.999366,0.999736,0.998903,0.99754]
average_cost
0
f_measure
0.973705454864435 [0.990975,0.977391,0.988257,0.967515,0.972687,0.977538,0.984698,0.977072,0.961226,0.940035]
kappa
0.9707389069777203
kb_relative_information_score
0.9740847239071584
mean_absolute_error
0.005669068978854522
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9736654804270463 [0.990975,0.984238,0.982047,0.963287,0.971831,0.97491,0.980287,0.978799,0.962094,0.948399]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9737875804283169 [0.990975,0.970639,0.994545,0.971781,0.973545,0.98018,0.98915,0.975352,0.96036,0.931818]
predictive_accuracy
0.9736654804270463
prior_entropy
3.3218327251668773
relative_absolute_error
0.03149528997177781
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.06588877851580847
root_relative_squared_error
0.2196308765417666
total_cost
0
unweighted_recall
0.9736865444230872 [0.990975,0.984238,0.982047,0.963287,0.971831,0.97491,0.980287,0.978799,0.962094,0.948399]
area_under_roc_curve
0.9995952932167634 [1,0.999687,0.999965,0.999829,0.998645,1,0.999647,0.999859,0.999498,0.998835]
area_under_roc_curve
0.9995948605998061 [0.999964,0.999896,0.999929,0.998426,0.999444,0.999929,0.999718,0.999929,0.999857,0.998906]
area_under_roc_curve
0.9998029842114555 [1,1,1,0.999479,0.999931,1,1,1,0.999857,0.998765]
area_under_roc_curve
0.9996271510250728 [1,0.999826,0.999541,0.999305,1,1,1,1,0.999606,0.997988]
area_under_roc_curve
0.9997853037635882 [0.999928,1,1,0.999861,0.999965,0.999964,1,0.999896,0.999498,0.998749]
area_under_roc_curve
0.9990191234116906 [0.999211,0.999722,0.999824,0.999375,0.998923,0.997382,0.999647,0.999931,0.998063,0.998055]
area_under_roc_curve
0.9994336799129303 [0.999965,0.999965,1,0.999896,1,0.999894,0.999857,0.999201,0.999965,0.995589]
area_under_roc_curve
0.9985744023508643 [0.999929,0.999236,0.999749,0.994789,0.999618,0.999541,1,0.999097,0.997741,0.996118]
area_under_roc_curve
0.9991838183299283 [1,0.99935,0.999749,0.99934,0.999965,0.998094,1,0.999824,0.997494,0.998024]
area_under_roc_curve
0.9986880801649715 [0.999965,0.998715,1,1,0.999612,0.999894,0.990824,0.999824,0.999118,0.998906]
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
0.9731368851003157 [1,0.965517,0.99115,0.983051,0.936937,0.99115,0.972973,0.990991,0.955752,0.944444]
f_measure
0.9680024608264916 [0.981818,0.982143,0.982143,0.929825,0.964912,0.982456,0.990991,0.972973,0.964286,0.929825]
f_measure
0.9839333961202741 [1,0.991304,0.990991,0.973913,0.982456,1,1,0.982759,0.962963,0.954955]
f_measure
0.9767973763740116 [1,0.974359,0.981818,0.964912,0.982759,0.981818,0.99115,0.99115,0.972973,0.927273]
f_measure
0.9804225721719483 [0.981481,0.982759,0.990991,0.982759,0.982759,0.990826,0.990991,0.982456,0.963636,0.955752]
f_measure
0.9697346941773491 [0.981818,0.973913,0.981818,0.973913,0.956522,0.953271,0.972973,0.982456,0.954128,0.966102]
f_measure
0.9804664043423569 [0.990991,0.99115,1,0.972973,1,0.965517,0.972477,0.965517,0.99115,0.954955]
f_measure
0.9595678568580774 [0.99115,0.982143,0.981818,0.925926,0.972973,0.955752,0.990991,0.956522,0.954128,0.885246]
f_measure
0.9734888754353112 [0.99115,0.982759,0.981481,0.964912,0.981818,0.981818,1,0.973451,0.946429,0.931034]
f_measure
0.9715792230200073 [0.99115,0.949153,1,1,0.964912,0.972477,0.963636,0.972973,0.946429,0.954955]
kappa
0.9703432165824691
kappa
0.964412861464856
kappa
0.9822056795474374
kappa
0.9742973639494672
kappa
0.9782510800579783
kappa
0.9663876780619264
kappa
0.9782519216900318
kappa
0.9545283450301655
kappa
0.9703432165824691
kappa
0.9683663202628635
kb_relative_information_score
0.9741816086578473
kb_relative_information_score
0.972595934526965
kb_relative_information_score
0.985544466033095
kb_relative_information_score
0.9804639158285272
kb_relative_information_score
0.9793942159627966
kb_relative_information_score
0.9678643483612344
kb_relative_information_score
0.9798104063661256
kb_relative_information_score
0.9570863635958412
kb_relative_information_score
0.9723622997515173
kb_relative_information_score
0.9715438927350303
mean_absolute_error
0.005610976864060947
mean_absolute_error
0.006561746061501355
mean_absolute_error
0.0032429694902238663
mean_absolute_error
0.004266686445489642
mean_absolute_error
0.004331059926014835
mean_absolute_error
0.006971795743840982
mean_absolute_error
0.00426557824952991
mean_absolute_error
0.009075652620319402
mean_absolute_error
0.005928290125148535
mean_absolute_error
0.006435934262415852
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
0.9736728289087674 [1,0.949153,0.982456,0.966667,0.962963,0.982456,0.981818,1,0.931034,0.980769]
precision
0.968365334151094 [0.981818,1,0.982143,0.946429,0.964912,0.965517,1,0.981818,0.947368,0.913793]
precision
0.9840665858766553 [1,0.982759,1,0.965517,0.982456,1,1,0.966102,0.981132,0.963636]
precision
0.9771529246342024 [1,0.95,1,0.964912,0.966102,1,0.982456,1,0.964286,0.944444]
precision
0.9807254013252565 [1,0.966102,1,0.966102,0.966102,1,1,0.982456,0.963636,0.964286]
precision
0.9702314476409759 [0.981818,0.965517,1,0.965517,0.948276,0.980769,0.981818,0.982456,0.962963,0.934426]
precision
0.9810160556702632 [1,1,1,1,1,0.933333,0.981481,0.949153,0.982456,0.963636]
precision
0.9622485546355125 [0.982456,1,0.981818,0.980392,1,0.947368,0.982143,0.948276,0.981132,0.818182]
precision
0.9741150028095149 [0.982456,0.982759,1,0.964912,1,1,1,0.964912,0.946429,0.9]
precision
0.9721659759722203 [0.982456,0.918033,1,1,0.948276,1,0.981481,0.981818,0.946429,0.963636]
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9679715302491103
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9804270462633453
predictive_accuracy
0.9697508896797153
predictive_accuracy
0.9804270462633453
predictive_accuracy
0.9590747330960854
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9715302491103204
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
0.031172651975188686
relative_absolute_error
0.03645479767255817
relative_absolute_error
0.018016781877774838
relative_absolute_error
0.023704188171051452
relative_absolute_error
0.024061858069336292
relative_absolute_error
0.0387328650589837
relative_absolute_error
0.02369797317511838
relative_absolute_error
0.05042096516849138
relative_absolute_error
0.03293532681030488
relative_absolute_error
0.035755428912658156
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
0.06604988122440737
root_mean_squared_error
0.06426394983051817
root_mean_squared_error
0.04970094153046699
root_mean_squared_error
0.05775790028257571
root_mean_squared_error
0.0606413475627431
root_mean_squared_error
0.07537443763321652
root_mean_squared_error
0.058131888559014425
root_mean_squared_error
0.0830336246716608
root_mean_squared_error
0.06902725785986799
root_mean_squared_error
0.0686831139906641
root_relative_squared_error
0.2201686008356044
root_relative_squared_error
0.2142154331857637
root_relative_squared_error
0.16567120936037155
root_relative_squared_error
0.1925279661767437
root_relative_squared_error
0.20213982252379595
root_relative_squared_error
0.25125060801534915
root_relative_squared_error
0.19377412799556296
root_relative_squared_error
0.2767804145693271
root_relative_squared_error
0.23009184022043988
root_relative_squared_error
0.2289435635320304
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
0.9733697881066302 [1,0.982456,1,1,0.912281,1,0.964286,0.982143,0.981818,0.910714]
unweighted_recall
0.9682254028488148 [0.981818,0.964912,0.982143,0.913793,0.964912,1,0.982143,0.964286,0.981818,0.946429]
unweighted_recall
0.9838938254727727 [1,1,0.982143,0.982456,0.982456,1,1,1,0.945455,0.946429]
unweighted_recall
0.9768472317156529 [1,1,0.964286,0.964912,1,0.964286,1,0.982456,0.981818,0.910714]
unweighted_recall
0.980320118478013 [0.963636,1,0.982143,1,1,0.981818,0.982143,0.982456,0.963636,0.947368]
unweighted_recall
0.9695397584871269 [0.981818,0.982456,0.964286,0.982456,0.964912,0.927273,0.964286,0.982456,0.945455,1]
unweighted_recall
0.9804488493962179 [0.982143,0.982456,1,0.947368,1,1,0.963636,0.982456,1,0.946429]
unweighted_recall
0.9593347003873319 [1,0.964912,0.981818,0.877193,0.947368,0.964286,1,0.964912,0.928571,0.964286]
unweighted_recall
0.9732735836456344 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.946429,0.964286]
unweighted_recall
0.9714598997493734 [1,0.982456,1,1,0.982143,0.946429,0.946429,0.964286,0.946429,0.946429]
usercpu_time_millis
5356.717668000783
usercpu_time_millis
3015.9322370000154
usercpu_time_millis
6314.427077999426
usercpu_time_millis
5609.440872998675
usercpu_time_millis
6330.500776999543
usercpu_time_millis
5703.860969000743
usercpu_time_millis
4522.319555999275
usercpu_time_millis
2731.4081360000273
usercpu_time_millis
4686.878761000116
usercpu_time_millis
2889.531236000039
usercpu_time_millis_testing
4.9641999994491925
usercpu_time_millis_testing
4.544400000668247
usercpu_time_millis_testing
4.680901000028825
usercpu_time_millis_testing
4.605500000252505
usercpu_time_millis_testing
5.0152000003436115
usercpu_time_millis_testing
4.589399999531452
usercpu_time_millis_testing
5.177301000003354
usercpu_time_millis_testing
3.7979999997332925
usercpu_time_millis_testing
4.515200000241748
usercpu_time_millis_testing
5.016799999793875
usercpu_time_millis_training
5351.753468001334
usercpu_time_millis_training
3011.387836999347
usercpu_time_millis_training
6309.746176999397
usercpu_time_millis_training
5604.835372998423
usercpu_time_millis_training
6325.485576999199
usercpu_time_millis_training
5699.271569001212
usercpu_time_millis_training
4517.142254999271
usercpu_time_millis_training
2727.610136000294
usercpu_time_millis_training
4682.363560999875
usercpu_time_millis_training
2884.514436000245
wall_clock_time_millis
5360.321521759033
wall_clock_time_millis
3016.401767730713
wall_clock_time_millis
6316.944122314453
wall_clock_time_millis
5614.232778549194
wall_clock_time_millis
6340.231895446777
wall_clock_time_millis
5716.985702514648
wall_clock_time_millis
4529.479742050171
wall_clock_time_millis
2739.020586013794
wall_clock_time_millis
4696.930408477783
wall_clock_time_millis
2890.9225463867188
wall_clock_time_millis_testing
4.96983528137207
wall_clock_time_millis_testing
4.548311233520508
wall_clock_time_millis_testing
4.683256149291992
wall_clock_time_millis_testing
4.611730575561523
wall_clock_time_millis_testing
5.018949508666992
wall_clock_time_millis_testing
4.593133926391602
wall_clock_time_millis_testing
5.180835723876953
wall_clock_time_millis_testing
3.7992000579833984
wall_clock_time_millis_testing
4.51970100402832
wall_clock_time_millis_testing
5.0201416015625
wall_clock_time_millis_training
5355.351686477661
wall_clock_time_millis_training
3011.8534564971924
wall_clock_time_millis_training
6312.260866165161
wall_clock_time_millis_training
5609.621047973633
wall_clock_time_millis_training
6335.21294593811
wall_clock_time_millis_training
5712.392568588257
wall_clock_time_millis_training
4524.298906326294
wall_clock_time_millis_training
2735.2213859558105
wall_clock_time_millis_training
4692.410707473755
wall_clock_time_millis_training
2885.9024047851562
weighted_recall
0.9733096085409253 [1,0.982456,1,1,0.912281,1,0.964286,0.982143,0.981818,0.910714]
weighted_recall
0.9679715302491103 [0.981818,0.964912,0.982143,0.913793,0.964912,1,0.982143,0.964286,0.981818,0.946429]
weighted_recall
0.9839857651245552 [1,1,0.982143,0.982456,0.982456,1,1,1,0.945455,0.946429]
weighted_recall
0.9768683274021353 [1,1,0.964286,0.964912,1,0.964286,1,0.982456,0.981818,0.910714]
weighted_recall
0.9804270462633452 [0.963636,1,0.982143,1,1,0.981818,0.982143,0.982456,0.963636,0.947368]
weighted_recall
0.9697508896797153 [0.981818,0.982456,0.964286,0.982456,0.964912,0.927273,0.964286,0.982456,0.945455,1]
weighted_recall
0.9804270462633452 [0.982143,0.982456,1,0.947368,1,1,0.963636,0.982456,1,0.946429]
weighted_recall
0.9590747330960854 [1,0.964912,0.981818,0.877193,0.947368,0.964286,1,0.964912,0.928571,0.964286]
weighted_recall
0.9733096085409253 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.946429,0.964286]
weighted_recall
0.9715302491103203 [1,0.982456,1,1,0.982143,0.946429,0.946429,0.964286,0.946429,0.946429]