10578706
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)
8294988
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
0.5260667032632056
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1100
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
58
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
17
19038
random_state
56901
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.06474124040417588
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
22083679
description
https://api.openml.org/data/download/22083679/description.xml
-1
22083680
predictions
https://api.openml.org/data/download/22083680/predictions.arff
area_under_roc_curve
0.9996980953994263 [0.99998,0.999658,0.999979,0.999736,0.999601,0.999705,0.999825,0.999888,0.999379,0.999233]
average_cost
0
f_measure
0.9820363613413894 [0.993677,0.97561,0.9955,0.979807,0.986831,0.980251,0.984726,0.988546,0.972924,0.9627]
kappa
0.980031285328138
kb_relative_information_score
0.9818760695979408
mean_absolute_error
0.004063321046846526
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9820284697508896 [0.99278,0.980736,0.992819,0.975524,0.989437,0.978495,0.982079,0.991166,0.972924,0.964413]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9820605411179174 [0.994575,0.970537,0.998195,0.984127,0.984238,0.982014,0.987387,0.98594,0.972924,0.960993]
predictive_accuracy
0.9820284697508898
prior_entropy
3.3218327251668773
relative_absolute_error
0.022574337178856742
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.05449903176978288
root_relative_squared_error
0.18166477491160585
total_cost
0
unweighted_recall
0.9820371655308809 [0.99278,0.980736,0.992819,0.975524,0.989437,0.978495,0.982079,0.991166,0.972924,0.964413]
area_under_roc_curve
0.9994365973601222 [1,0.999514,1,0.999863,0.9967,1,0.999682,0.999682,0.999713,0.999259]
area_under_roc_curve
0.9999084378556727 [1,0.999896,1,0.999692,1,0.999965,1,1,0.999928,0.999612]
area_under_roc_curve
0.9998698260116853 [1,0.999965,0.999965,0.999722,0.999931,1,1,1,0.999928,0.999188]
area_under_roc_curve
0.9997958050485539 [1,0.999722,0.999965,0.999097,1,1,1,1,1,0.999188]
area_under_roc_curve
0.9998311578546494 [1,0.999722,1,1,1,0.999713,0.999612,1,0.999749,0.999514]
area_under_roc_curve
0.9994198832058289 [0.999928,0.999826,1,0.999722,0.99927,0.998781,0.999541,0.999826,0.998279,0.998993]
area_under_roc_curve
0.9998029075865077 [0.999965,0.999792,1,0.999757,1,0.999894,0.999821,0.999444,1,0.999365]
area_under_roc_curve
0.9997677215725551 [1,0.999653,0.999928,0.999687,0.999896,0.999612,1,0.999757,0.999859,0.999294]
area_under_roc_curve
0.9994440966999553 [1,0.99935,0.999928,0.999792,1,0.998694,1,1,0.9982,0.998482]
area_under_roc_curve
0.9998417287187483 [0.999965,0.999861,1,1,1,1,0.999753,1,0.998941,0.999894]
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
0.9715032894409232 [1,0.964912,1,0.974359,0.955752,1,0.964286,0.964286,0.947368,0.944444]
f_measure
0.9875748791292329 [1,0.973451,1,0.982456,1,0.973913,1,0.990991,0.981818,0.973451]
f_measure
0.9874751204532267 [1,0.99115,0.99115,0.973913,0.991304,0.990991,1,0.991304,0.982143,0.962963]
f_measure
0.991133441587687 [1,0.991304,0.990991,0.982143,1,0.990991,0.99115,1,1,0.964912]
f_measure
0.9821545109097318 [0.990826,0.982759,1,1,0.982759,0.981818,0.972477,0.991304,0.963636,0.955752]
f_measure
0.9680124251350453 [0.990826,0.966102,0.990991,0.964912,0.948276,0.952381,0.982143,0.982456,0.953271,0.949153]
f_measure
0.9786935377215285 [0.990991,0.955752,1,0.973451,1,0.964912,0.963636,0.982456,0.990991,0.964912]
f_measure
0.9839845223932283 [0.99115,0.982143,0.990826,0.973451,0.99115,0.982143,0.990991,0.982759,0.982143,0.973451]
f_measure
0.982266190141703 [0.99115,0.982759,0.990826,0.973451,1,0.981818,1,1,0.946429,0.956522]
f_measure
0.9875992793866071 [0.982143,0.966102,1,1,1,0.982456,0.981818,1,0.981818,0.981818]
kappa
0.9683664315491372
kappa
0.9861604111772093
kappa
0.9861602651150028
kappa
0.9901145098591053
kappa
0.9802284632731392
kappa
0.964409480954006
kappa
0.9762749071259709
kappa
0.9822061803444783
kappa
0.9802289501642896
kappa
0.9861602651150028
kb_relative_information_score
0.9724470339866113
kb_relative_information_score
0.9851893805335032
kb_relative_information_score
0.9873889262101035
kb_relative_information_score
0.9902865239464742
kb_relative_information_score
0.984357429261111
kb_relative_information_score
0.969608067355191
kb_relative_information_score
0.9817301480921325
kb_relative_information_score
0.9799804315105501
kb_relative_information_score
0.9803705097224245
kb_relative_information_score
0.9874019888290332
mean_absolute_error
0.005798852691284966
mean_absolute_error
0.0033426885803235417
mean_absolute_error
0.003060599143044274
mean_absolute_error
0.002381821185879325
mean_absolute_error
0.0035638466071348297
mean_absolute_error
0.006429764266426861
mean_absolute_error
0.003968280060448719
mean_absolute_error
0.004532661163589731
mean_absolute_error
0.00481034119101237
mean_absolute_error
0.0027443555793206413
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
0.9719933167140477 [1,0.964912,1,0.966102,0.964286,1,0.964286,0.964286,0.915254,0.980769]
precision
0.9878465710842039 [1,0.982143,1,1,1,0.949153,1,1,0.981818,0.964912]
precision
0.9878232825898345 [1,1,0.982456,0.965517,0.982759,1,1,0.982759,0.964912,1]
precision
0.9913491699551985 [1,0.982759,1,1,1,1,0.982456,1,1,0.948276]
precision
0.982414804829066 [1,0.966102,1,1,0.966102,0.981818,1,0.982759,0.963636,0.964286]
precision
0.969160257735005 [1,0.934426,1,0.964912,0.932203,1,0.982143,0.982456,0.980769,0.918033]
precision
0.9789205073365708 [1,0.964286,1,0.982143,1,0.948276,0.963636,0.982456,1,0.948276]
precision
0.9842000501585709 [0.982456,1,1,0.982143,1,0.982143,0.982143,0.966102,0.982143,0.964912]
precision
0.982567751863524 [0.982456,0.982759,1,0.982143,1,1,1,1,0.946429,0.932203]
precision
0.9881339156569547 [0.982143,0.934426,1,1,1,0.965517,1,1,1,1]
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9911032028469751
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9679715302491103
predictive_accuracy
0.9786476868327402
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9875444839857651
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
0.032216425264313654
relative_absolute_error
0.018570824706706807
relative_absolute_error
0.017003597271501542
relative_absolute_error
0.013232549028664614
relative_absolute_error
0.019799488510118163
relative_absolute_error
0.03572152725681851
relative_absolute_error
0.022046294528586984
relative_absolute_error
0.02518178694259987
relative_absolute_error
0.02672442742351347
relative_absolute_error
0.01524652161232962
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
0.06846263912130551
root_mean_squared_error
0.04671191042028913
root_mean_squared_error
0.04335194251993804
root_mean_squared_error
0.03986621142576647
root_mean_squared_error
0.05075725312409547
root_mean_squared_error
0.07256421789534408
root_mean_squared_error
0.05279433892444426
root_mean_squared_error
0.05840643982121891
root_mean_squared_error
0.056198606897339555
root_mean_squared_error
0.04652849727261792
root_relative_squared_error
0.22821121227513597
root_relative_squared_error
0.15570801595616987
root_relative_squared_error
0.14450769993958235
root_relative_squared_error
0.1328884978059074
root_relative_squared_error
0.16919251551401268
root_relative_squared_error
0.24188311633026316
root_relative_squared_error
0.17598218880848687
root_relative_squared_error
0.19468930437710694
root_relative_squared_error
0.18732948808548677
root_relative_squared_error
0.15509488944883099
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
0.9716143218547938 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.964286,0.981818,0.910714]
unweighted_recall
0.9876533418184961 [1,0.964912,1,0.965517,1,1,1,0.982143,0.981818,0.982143]
unweighted_recall
0.987562656641604 [1,0.982456,1,0.982456,1,0.982143,1,1,1,0.928571]
unweighted_recall
0.9911340852130326 [1,1,0.982143,0.964912,1,0.982143,1,1,1,0.982143]
unweighted_recall
0.9821069719753931 [0.981818,1,1,1,1,0.981818,0.946429,1,0.963636,0.947368]
unweighted_recall
0.9677204374572795 [0.981818,1,0.982143,0.964912,0.964912,0.909091,0.982143,0.982456,0.927273,0.982456]
unweighted_recall
0.9786944634313055 [0.982143,0.947368,1,0.964912,1,0.982143,0.963636,0.982456,0.982143,0.982143]
unweighted_recall
0.9840527455001139 [1,0.964912,0.981818,0.964912,0.982456,0.982143,1,1,0.982143,0.982143]
unweighted_recall
0.9822346226066735 [1,0.982759,0.981818,0.964912,1,0.964286,1,1,0.946429,0.982143]
unweighted_recall
0.9875 [0.982143,1,1,1,1,1,0.964286,1,0.964286,0.964286]
usercpu_time_millis
8258.212202999857
usercpu_time_millis
7786.879593000776
usercpu_time_millis
8336.39510499961
usercpu_time_millis
9001.078909999706
usercpu_time_millis
8327.151113000582
usercpu_time_millis
9454.242018000514
usercpu_time_millis
7975.301497001055
usercpu_time_millis
10096.355525000035
usercpu_time_millis
7606.885092000084
usercpu_time_millis
9946.915423999599
usercpu_time_millis_testing
6.504999999378924
usercpu_time_millis_testing
6.522600000607781
usercpu_time_millis_testing
6.827600000178791
usercpu_time_millis_testing
5.66880000042147
usercpu_time_millis_testing
5.694299999959185
usercpu_time_millis_testing
5.934799999522511
usercpu_time_millis_testing
6.464699999924051
usercpu_time_millis_testing
5.90840000040771
usercpu_time_millis_testing
6.721599998854799
usercpu_time_millis_testing
6.1332999994192505
usercpu_time_millis_training
8251.707203000478
usercpu_time_millis_training
7780.356993000169
usercpu_time_millis_training
8329.567504999432
usercpu_time_millis_training
8995.410109999284
usercpu_time_millis_training
8321.456813000623
usercpu_time_millis_training
9448.307218000991
usercpu_time_millis_training
7968.836797001131
usercpu_time_millis_training
10090.447124999628
usercpu_time_millis_training
7600.163492001229
usercpu_time_millis_training
9940.78212400018
wall_clock_time_millis
8262.702703475952
wall_clock_time_millis
7790.034770965576
wall_clock_time_millis
8342.128992080688
wall_clock_time_millis
9016.889333724976
wall_clock_time_millis
8379.305839538574
wall_clock_time_millis
9464.694738388062
wall_clock_time_millis
7987.241744995117
wall_clock_time_millis
10099.377155303955
wall_clock_time_millis
7615.233659744263
wall_clock_time_millis
9949.33009147644
wall_clock_time_millis_testing
6.508827209472656
wall_clock_time_millis_testing
6.526470184326172
wall_clock_time_millis_testing
6.83283805847168
wall_clock_time_millis_testing
5.668401718139648
wall_clock_time_millis_testing
5.698680877685547
wall_clock_time_millis_testing
5.938291549682617
wall_clock_time_millis_testing
6.4678192138671875
wall_clock_time_millis_testing
5.912065505981445
wall_clock_time_millis_testing
6.725788116455078
wall_clock_time_millis_testing
6.136417388916016
wall_clock_time_millis_training
8256.19387626648
wall_clock_time_millis_training
7783.50830078125
wall_clock_time_millis_training
8335.296154022217
wall_clock_time_millis_training
9011.220932006836
wall_clock_time_millis_training
8373.607158660889
wall_clock_time_millis_training
9458.756446838379
wall_clock_time_millis_training
7980.77392578125
wall_clock_time_millis_training
10093.465089797974
wall_clock_time_millis_training
7608.507871627808
wall_clock_time_millis_training
9943.193674087524
weighted_recall
0.9715302491103203 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.964286,0.981818,0.910714]
weighted_recall
0.9875444839857651 [1,0.964912,1,0.965517,1,1,1,0.982143,0.981818,0.982143]
weighted_recall
0.9875444839857651 [1,0.982456,1,0.982456,1,0.982143,1,1,1,0.928571]
weighted_recall
0.9911032028469751 [1,1,0.982143,0.964912,1,0.982143,1,1,1,0.982143]
weighted_recall
0.9822064056939501 [0.981818,1,1,1,1,0.981818,0.946429,1,0.963636,0.947368]
weighted_recall
0.9679715302491103 [0.981818,1,0.982143,0.964912,0.964912,0.909091,0.982143,0.982456,0.927273,0.982456]
weighted_recall
0.9786476868327402 [0.982143,0.947368,1,0.964912,1,0.982143,0.963636,0.982456,0.982143,0.982143]
weighted_recall
0.9839857651245552 [1,0.964912,0.981818,0.964912,0.982456,0.982143,1,1,0.982143,0.982143]
weighted_recall
0.9822064056939501 [1,0.982759,0.981818,0.964912,1,0.964286,1,1,0.946429,0.982143]
weighted_recall
0.9875444839857651 [0.982143,1,1,1,1,1,0.964286,1,0.964286,0.964286]