10578906
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)
8295188
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
0.07443433148841704
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
947
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
113
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
13
19038
random_state
49994
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.37147477265999673
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
22084079
description
https://api.openml.org/data/download/22084079/description.xml
-1
22084080
predictions
https://api.openml.org/data/download/22084080/predictions.arff
area_under_roc_curve
0.9993067748284951 [0.999934,0.999291,0.999829,0.999503,0.999617,0.998829,0.999478,0.999736,0.999041,0.997808]
average_cost
0
f_measure
0.9731472560072313 [0.98913,0.969592,0.986499,0.969271,0.970976,0.979335,0.983871,0.976253,0.960145,0.946809]
kappa
0.9701457084464687
kb_relative_information_score
0.9633059540803156
mean_absolute_error
0.010698309007508408
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9731316725978648 [0.98556,0.977233,0.983842,0.965035,0.971831,0.976703,0.983871,0.980565,0.956679,0.950178]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9731929082136295 [0.992727,0.962069,0.98917,0.973545,0.970123,0.981982,0.983871,0.971979,0.963636,0.943463]
predictive_accuracy
0.9731316725978648
prior_entropy
3.3218327251668773
relative_absolute_error
0.05943592248673649
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.06532662037584569
root_relative_squared_error
0.21775700229767975
total_cost
0
unweighted_recall
0.9731495937234289 [0.98556,0.977233,0.983842,0.965035,0.971831,0.976703,0.983871,0.980565,0.956679,0.950178]
area_under_roc_curve
0.9993526527432283 [1,0.999653,0.999824,0.999453,0.999131,1,0.999047,0.999718,0.999175,0.99753]
area_under_roc_curve
0.9995528091920703 [1,0.999444,1,0.999213,0.998993,0.999718,1,0.999929,0.999785,0.998482]
area_under_roc_curve
0.9996798920906258 [1,0.999965,1,0.999618,0.999826,1,1,0.999965,0.999892,0.99753]
area_under_roc_curve
0.9994230462408217 [1,0.999375,0.999577,0.998819,1,0.999965,1,0.999757,0.999139,0.9976]
area_under_roc_curve
0.9995954320187501 [0.999892,0.999687,1,0.999965,0.999965,0.999175,0.999329,1,0.999641,0.998298]
area_under_roc_curve
0.9986608051721331 [0.999928,0.999618,0.999965,0.999375,0.999097,0.99419,0.999682,0.999375,0.997669,0.997603]
area_under_roc_curve
0.9996236067057682 [0.999824,0.999409,1,0.999792,1,0.999753,0.999677,0.999861,0.999294,0.998624]
area_under_roc_curve
0.9990394953331673 [0.999824,0.999131,0.999857,0.999201,0.999618,0.998588,0.999964,0.999409,0.999471,0.995342]
area_under_roc_curve
0.998765009653082 [1,0.998084,0.999103,0.999583,0.999859,0.997318,1,0.999682,0.997671,0.996365]
area_under_roc_curve
0.9994477739588905 [0.999788,0.99934,1,1,0.999894,0.999929,0.997283,1,0.998588,0.999647]
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
0.9715887668495156 [1,0.973913,0.982143,0.982456,0.955752,1,0.955752,0.973451,0.938053,0.954128]
f_measure
0.9805312300452792 [1,0.982143,0.99115,0.956522,0.973913,0.982143,1,0.981818,0.990826,0.948276]
f_measure
0.9804014562973562 [0.981481,0.99115,0.99115,0.964912,0.965517,1,1,0.974359,0.981818,0.954128]
f_measure
0.9733538372996278 [1,0.948276,0.972973,0.964286,1,0.990991,0.99115,0.973451,0.964286,0.928571]
f_measure
0.9768248515310588 [0.981481,0.965517,1,0.982759,0.974359,0.990826,0.981818,0.991304,0.944444,0.955752]
f_measure
0.9536843041960332 [0.981818,0.966102,0.972477,0.948276,0.93913,0.934579,0.982143,0.982456,0.915888,0.913793]
f_measure
0.9769594851101855 [0.990991,0.965517,0.990991,0.982143,0.99115,0.964912,0.963636,0.982456,0.981818,0.955752]
f_measure
0.9679520054710815 [0.99115,0.982143,0.981818,0.954955,0.955752,0.964286,0.990991,0.93913,0.955752,0.964912]
f_measure
0.9716931971026908 [0.99115,0.965517,0.990826,0.964912,0.972477,0.981818,1,0.973451,0.946429,0.931034]
f_measure
0.978655412887051 [0.972973,0.957265,0.990991,0.991304,0.982143,0.982456,0.972973,0.99115,0.981818,0.963636]
kappa
0.9683668766864023
kappa
0.9782518451807186
kappa
0.9782513861135347
kappa
0.9703437382368773
kappa
0.9742963692654095
kappa
0.9485921959491551
kappa
0.9742978160531353
kappa
0.964412861464856
kappa
0.9683662089758067
kappa
0.9762747401971476
kb_relative_information_score
0.96004331249797
kb_relative_information_score
0.9682714114566879
kb_relative_information_score
0.9688571083623623
kb_relative_information_score
0.962312079765467
kb_relative_information_score
0.9685523877942768
kb_relative_information_score
0.9493997491130882
kb_relative_information_score
0.9659930660405113
kb_relative_information_score
0.9586557685287219
kb_relative_information_score
0.9605820133221442
kb_relative_information_score
0.9703924208625277
mean_absolute_error
0.011650194982424058
mean_absolute_error
0.009613552759436357
mean_absolute_error
0.009945632928826864
mean_absolute_error
0.011037350667872729
mean_absolute_error
0.009305047941168541
mean_absolute_error
0.013607840460057414
mean_absolute_error
0.010343491447397785
mean_absolute_error
0.011184427553078002
mean_absolute_error
0.011423046891495255
mean_absolute_error
0.008872504443327189
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
0.972043602646303 [1,0.965517,0.982143,1,0.964286,1,0.947368,0.964912,0.913793,0.981132]
precision
0.9810503064631759 [1,1,0.982456,0.964912,0.965517,0.982143,1,1,1,0.916667]
precision
0.9808054003582178 [1,1,0.982456,0.964912,0.949153,1,1,0.95,0.981818,0.981132]
precision
0.9736405651965839 [1,0.932203,0.981818,0.981818,1,1,0.982456,0.982143,0.947368,0.928571]
precision
0.9772696564428941 [1,0.949153,1,0.966102,0.95,1,1,0.982759,0.962264,0.964286]
precision
0.9544159824049726 [0.981818,0.934426,1,0.932203,0.931034,0.961538,0.982143,0.982456,0.942308,0.898305]
precision
0.9773587756457667 [1,0.949153,0.982143,1,1,0.948276,0.963636,0.982456,1,0.947368]
precision
0.9682725561090519 [0.982456,1,0.981818,0.981481,0.964286,0.964286,0.982143,0.931034,0.947368,0.948276]
precision
0.9723356433789099 [0.982456,0.965517,1,0.964912,1,1,1,0.964912,0.946429,0.9]
precision
0.9790575624249114 [0.981818,0.933333,1,0.982759,0.982143,0.965517,0.981818,0.982456,1,0.981481]
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.9804270462633453
predictive_accuracy
0.9804270462633453
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9537366548042705
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9679715302491103
predictive_accuracy
0.9715302491103204
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
0.06472446463936264
relative_absolute_error
0.053409582979126895
relative_absolute_error
0.0552543894277337
relative_absolute_error
0.061319583823111465
relative_absolute_error
0.05169560031804565
relative_absolute_error
0.07560041453440554
relative_absolute_error
0.057464608200426905
relative_absolute_error
0.062136537797919236
relative_absolute_error
0.06346210704919018
relative_absolute_error
0.04929202023600948
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
0.06992889397163898
root_mean_squared_error
0.05688534940384161
root_mean_squared_error
0.05700813752844789
root_mean_squared_error
0.0651382297048821
root_mean_squared_error
0.059365228239800415
root_mean_squared_error
0.08098288251416572
root_mean_squared_error
0.061659094117581685
root_mean_squared_error
0.07188142804364957
root_mean_squared_error
0.06864374541104099
root_mean_squared_error
0.05738953250845109
root_relative_squared_error
0.23309878016900595
root_relative_squared_error
0.18961983813015806
root_relative_squared_error
0.19002873581239388
root_relative_squared_error
0.21712927277617514
root_relative_squared_error
0.19788604941639715
root_relative_squared_error
0.26994560900780856
root_relative_squared_error
0.20553155061359157
root_relative_squared_error
0.2396062020949789
root_relative_squared_error
0.22881345994235908
root_relative_squared_error
0.19129831655140211
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
0.9716121023562041 [1,0.982456,0.982143,0.965517,0.947368,1,0.964286,0.982143,0.963636,0.928571]
unweighted_recall
0.9806033893511208 [1,0.964912,1,0.948276,0.982456,0.982143,1,0.964286,0.981818,0.982143]
unweighted_recall
0.9803850535429482 [0.963636,0.982456,1,0.964912,0.982456,1,1,1,0.981818,0.928571]
unweighted_recall
0.9734011164274323 [1,0.964912,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.928571]
unweighted_recall
0.9766837548416495 [0.963636,0.982456,1,1,1,0.981818,0.964286,1,0.927273,0.947368]
unweighted_recall
0.9534951013898383 [0.981818,1,0.946429,0.964912,0.947368,0.909091,0.982143,0.982456,0.890909,0.929825]
unweighted_recall
0.976877420824789 [0.982143,0.982456,1,0.964912,0.982456,0.982143,0.963636,0.982456,0.964286,0.964286]
unweighted_recall
0.9682006151742995 [1,0.964912,0.981818,0.929825,0.947368,0.964286,1,0.947368,0.964286,0.982143]
unweighted_recall
0.9715819132470674 [1,0.965517,0.981818,0.964912,0.946429,0.964286,1,0.982143,0.946429,0.964286]
unweighted_recall
0.9786027568922305 [0.964286,0.982456,0.982143,1,0.982143,1,0.964286,1,0.964286,0.946429]
usercpu_time_millis
10858.471133999046
usercpu_time_millis
10901.70973399836
usercpu_time_millis
10870.544438001161
usercpu_time_millis
10918.619535999824
usercpu_time_millis
10871.534834999693
usercpu_time_millis
10859.485332000986
usercpu_time_millis
10792.338036000729
usercpu_time_millis
10922.610926998459
usercpu_time_millis
10933.503832000497
usercpu_time_millis
10930.150337000669
usercpu_time_millis_testing
9.871300999293453
usercpu_time_millis_testing
9.613999998691725
usercpu_time_millis_testing
9.931901000527432
usercpu_time_millis_testing
9.59100000000035
usercpu_time_millis_testing
10.528700000577373
usercpu_time_millis_testing
9.940100000676466
usercpu_time_millis_testing
10.36740000017744
usercpu_time_millis_testing
8.447199999864097
usercpu_time_millis_testing
8.150401001330465
usercpu_time_millis_testing
8.510501000273507
usercpu_time_millis_training
10848.599832999753
usercpu_time_millis_training
10892.095733999668
usercpu_time_millis_training
10860.612537000634
usercpu_time_millis_training
10909.028535999823
usercpu_time_millis_training
10861.006134999116
usercpu_time_millis_training
10849.54523200031
usercpu_time_millis_training
10781.970636000551
usercpu_time_millis_training
10914.163726998595
usercpu_time_millis_training
10925.353430999166
usercpu_time_millis_training
10921.639836000395
wall_clock_time_millis
10861.895561218262
wall_clock_time_millis
10921.42105102539
wall_clock_time_millis
10876.709461212158
wall_clock_time_millis
10924.063205718994
wall_clock_time_millis
10898.382425308228
wall_clock_time_millis
10870.140552520752
wall_clock_time_millis
10803.423166275024
wall_clock_time_millis
10957.184076309204
wall_clock_time_millis
10988.389015197754
wall_clock_time_millis
10937.669038772583
wall_clock_time_millis_testing
9.874105453491211
wall_clock_time_millis_testing
9.617090225219727
wall_clock_time_millis_testing
9.932756423950195
wall_clock_time_millis_testing
9.596109390258789
wall_clock_time_millis_testing
10.536670684814453
wall_clock_time_millis_testing
9.943962097167969
wall_clock_time_millis_testing
10.372161865234375
wall_clock_time_millis_testing
8.450984954833984
wall_clock_time_millis_testing
8.152484893798828
wall_clock_time_millis_testing
8.513212203979492
wall_clock_time_millis_training
10852.02145576477
wall_clock_time_millis_training
10911.80396080017
wall_clock_time_millis_training
10866.776704788208
wall_clock_time_millis_training
10914.467096328735
wall_clock_time_millis_training
10887.845754623413
wall_clock_time_millis_training
10860.196590423584
wall_clock_time_millis_training
10793.05100440979
wall_clock_time_millis_training
10948.73309135437
wall_clock_time_millis_training
10980.236530303955
wall_clock_time_millis_training
10929.155826568604
weighted_recall
0.9715302491103203 [1,0.982456,0.982143,0.965517,0.947368,1,0.964286,0.982143,0.963636,0.928571]
weighted_recall
0.9804270462633452 [1,0.964912,1,0.948276,0.982456,0.982143,1,0.964286,0.981818,0.982143]
weighted_recall
0.9804270462633452 [0.963636,0.982456,1,0.964912,0.982456,1,1,1,0.981818,0.928571]
weighted_recall
0.9733096085409253 [1,0.964912,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.928571]
weighted_recall
0.9768683274021353 [0.963636,0.982456,1,1,1,0.981818,0.964286,1,0.927273,0.947368]
weighted_recall
0.9537366548042705 [0.981818,1,0.946429,0.964912,0.947368,0.909091,0.982143,0.982456,0.890909,0.929825]
weighted_recall
0.9768683274021353 [0.982143,0.982456,1,0.964912,0.982456,0.982143,0.963636,0.982456,0.964286,0.964286]
weighted_recall
0.9679715302491103 [1,0.964912,0.981818,0.929825,0.947368,0.964286,1,0.947368,0.964286,0.982143]
weighted_recall
0.9715302491103203 [1,0.965517,0.981818,0.964912,0.946429,0.964286,1,0.982143,0.946429,0.964286]
weighted_recall
0.9786476868327402 [0.964286,0.982456,0.982143,1,0.982143,1,0.964286,1,0.964286,0.946429]