10578792
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)
8295074
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
0.5896905561900242
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1161
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
64
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
1514
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.09130627431122447
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
22083851
description
https://api.openml.org/data/download/22083851/description.xml
-1
22083852
predictions
https://api.openml.org/data/download/22083852/predictions.arff
area_under_roc_curve
0.9995683171675189 [0.999913,0.999532,0.999911,0.999672,0.999672,0.999712,0.999641,0.99975,0.999123,0.998756]
average_cost
0
f_measure
0.97884088768407 [0.991855,0.973958,0.990099,0.977273,0.978836,0.982014,0.989228,0.978873,0.96745,0.959147]
kappa
0.9764724250369451
kb_relative_information_score
0.978482965324468
mean_absolute_error
0.005184430784855969
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9788256227758008 [0.98917,0.982487,0.987433,0.977273,0.977113,0.978495,0.987455,0.982332,0.965704,0.960854]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9788813844631427 [0.994555,0.965577,0.99278,0.977273,0.980565,0.98556,0.991007,0.975439,0.969203,0.957447]
predictive_accuracy
0.9788256227758008
prior_entropy
3.3218327251668773
relative_absolute_error
0.028802816038524078
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.057714266215319436
root_relative_squared_error
0.1923823018633469
total_cost
0
unweighted_recall
0.9788314658524448 [0.98917,0.982487,0.987433,0.977273,0.977113,0.978495,0.987455,0.982332,0.965704,0.960854]
area_under_roc_curve
0.9996973839494859 [1,0.999861,0.999965,0.999966,0.998888,1,0.999718,0.999859,0.999641,0.999082]
area_under_roc_curve
0.9997852058049899 [1,1,0.999965,0.999179,0.999896,1,1,0.999965,0.999641,0.999224]
area_under_roc_curve
0.9995919233954913 [1,0.999965,0.999965,0.999375,0.999792,0.999965,1,1,0.999928,0.99693]
area_under_roc_curve
0.9995566951615906 [1,0.999409,0.999612,0.999062,0.999965,1,1,0.999931,0.999462,0.99813]
area_under_roc_curve
0.9998523612096875 [0.999785,0.999687,1,1,1,0.999964,0.999859,0.999931,0.999426,0.999861]
area_under_roc_curve
0.9992017747076275 [0.999928,0.999618,0.999965,0.999444,0.999236,0.998386,0.999506,0.999479,0.997812,0.99861]
area_under_roc_curve
0.9998450780626523 [1,0.999896,1,0.999653,1,1,0.999928,0.999409,0.999965,0.999612]
area_under_roc_curve
0.9996094990351535 [0.999894,0.999861,0.999964,0.999479,0.999965,0.999929,0.999964,0.999792,0.999718,0.99753]
area_under_roc_curve
0.9993913485880973 [1,0.999247,0.999641,0.999722,0.999718,0.9994,1,0.999824,0.998165,0.9982]
area_under_roc_curve
0.9996939304018596 [0.999965,0.999375,1,0.999965,0.999859,0.999894,0.999471,0.999965,0.999047,0.9994]
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
0.9750297813172518 [1,0.957265,0.99115,0.982456,0.955752,1,0.982143,0.973451,0.964286,0.944444]
f_measure
0.9786912081763545 [1,0.982143,0.982143,0.957265,0.982456,0.973913,1,0.981818,0.981818,0.946429]
f_measure
0.9874941468923111 [0.990826,0.99115,0.99115,0.991304,0.982143,0.99115,1,0.982759,0.990991,0.963636]
f_measure
0.9750845230160786 [1,0.965517,0.981818,0.973451,0.982759,0.981818,0.99115,0.982456,0.954955,0.936937]
f_measure
0.9875743767951991 [0.981481,0.991304,1,1,0.991304,0.990826,0.990991,0.982456,0.964286,0.982456]
f_measure
0.9626904319072075 [0.990826,0.941176,0.990991,0.947368,0.956522,0.943396,0.990991,0.982456,0.925926,0.957265]
f_measure
0.9875583929911227 [0.990991,0.973913,1,0.982456,1,0.982456,0.972477,0.99115,0.990991,0.99115]
f_measure
0.9769551648562738 [0.99115,0.982143,0.981818,0.964286,0.982143,0.990991,0.990991,0.957265,0.972973,0.956522]
f_measure
0.9787315711369589 [0.99115,0.982759,0.981481,0.982759,0.981818,0.981818,1,0.973451,0.963636,0.948276]
f_measure
0.978594026538418 [0.982143,0.974359,1,0.991304,0.973451,0.982143,0.972973,0.982143,0.963636,0.963636]
kappa
0.9723207249802994
kappa
0.9762745732659752
kappa
0.9861602651150028
kappa
0.972320335476971
kappa
0.9861600216711405
kappa
0.9584781660310445
kappa
0.9861602164269154
kappa
0.9742979968901491
kappa
0.9762744063324538
kappa
0.9762747401971476
kb_relative_information_score
0.9767427639015991
kb_relative_information_score
0.9806161239865996
kb_relative_information_score
0.9822004423387171
kb_relative_information_score
0.974989608735339
kb_relative_information_score
0.9861008111914655
kb_relative_information_score
0.9651749213374142
kb_relative_information_score
0.9870316074123798
kb_relative_information_score
0.9758697275501261
kb_relative_information_score
0.9752282603975925
kb_relative_information_score
0.9808752691015401
mean_absolute_error
0.005373455071969026
mean_absolute_error
0.005112855794361251
mean_absolute_error
0.0047325788664305535
mean_absolute_error
0.006621547768621796
mean_absolute_error
0.0032914400530476397
mean_absolute_error
0.007967869639914422
mean_absolute_error
0.0030999161850992288
mean_absolute_error
0.005778557398619548
mean_absolute_error
0.005501920808722725
mean_absolute_error
0.00436416626177349
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
0.975525368993247 [1,0.933333,0.982456,1,0.964286,1,0.982143,0.964912,0.947368,0.980769]
precision
0.9790095904457446 [1,1,0.982143,0.949153,0.982456,0.949153,1,1,0.981818,0.946429]
precision
0.9877241028729503 [1,1,0.982456,0.982759,1,0.982456,1,0.966102,0.982143,0.981481]
precision
0.9753882637299676 [1,0.949153,1,0.982143,0.966102,1,0.982456,0.982456,0.946429,0.945455]
precision
0.9877931422002055 [1,0.982759,1,1,0.982759,1,1,0.982456,0.947368,0.982456]
precision
0.9636013455266089 [1,0.903226,1,0.947368,0.948276,0.980392,1,0.982456,0.943396,0.933333]
precision
0.9877268213825493 [1,0.965517,1,0.982456,1,0.965517,0.981481,1,1,0.982456]
precision
0.9775520380399808 [0.982456,1,0.981818,0.981818,1,1,0.982143,0.933333,0.981818,0.932203]
precision
0.9793891894758241 [0.982456,0.982759,1,0.966102,1,1,1,0.964912,0.981481,0.916667]
precision
0.9788435466305208 [0.982143,0.95,1,0.982759,0.964912,0.982143,0.981818,0.982143,0.981481,0.981481]
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9786476868327402
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9626334519572954
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9786476868327402
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
0.029853062830412606
relative_absolute_error
0.028405263136586503
relative_absolute_error
0.026292520300571862
relative_absolute_error
0.03678695781756807
relative_absolute_error
0.018286092723966096
relative_absolute_error
0.04426670414763912
relative_absolute_error
0.017221986399544472
relative_absolute_error
0.032103525058638754
relative_absolute_error
0.0305665809355374
relative_absolute_error
0.024245529890991997
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
0.061446768908938444
root_mean_squared_error
0.051914902623196216
root_mean_squared_error
0.04858642917246733
root_mean_squared_error
0.059489565723823024
root_mean_squared_error
0.046860092627348124
root_mean_squared_error
0.07710193387369106
root_mean_squared_error
0.043912953188456706
root_mean_squared_error
0.060123809100918434
root_mean_squared_error
0.06377663336623761
root_mean_squared_error
0.056458815645473115
root_relative_squared_error
0.20482473073018131
root_relative_squared_error
0.17305150684876672
root_relative_squared_error
0.1619561366774186
root_relative_squared_error
0.19830023324100327
root_relative_squared_error
0.15620185216596977
root_relative_squared_error
0.2570089857146367
root_relative_squared_error
0.14637739152693785
root_relative_squared_error
0.2004139030933917
root_relative_squared_error
0.2125896839780676
root_relative_squared_error
0.18819592903766047
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
0.9752159984601001 [1,0.982456,1,0.965517,0.947368,1,0.982143,0.982143,0.981818,0.910714]
unweighted_recall
0.9787560987107267 [1,0.964912,0.982143,0.965517,0.982456,1,1,0.964286,0.981818,0.946429]
unweighted_recall
0.9875615174299386 [0.981818,0.982456,1,1,0.964912,1,1,1,1,0.946429]
unweighted_recall
0.975060378218273 [1,0.982456,0.964286,0.964912,1,0.964286,1,0.982456,0.963636,0.928571]
unweighted_recall
0.9874327865117338 [0.963636,1,1,1,1,0.981818,0.982143,0.982456,0.981818,0.982456]
unweighted_recall
0.9623934837092729 [0.981818,0.982456,0.982143,0.947368,0.964912,0.909091,0.982143,0.982456,0.909091,0.982456]
unweighted_recall
0.987529049897471 [0.982143,0.982456,1,0.982456,1,1,0.963636,0.982456,0.982143,1]
unweighted_recall
0.9770038733196627 [1,0.964912,0.981818,0.947368,0.964912,0.982143,1,0.982456,0.964286,0.982143]
unweighted_recall
0.9785680698611733 [1,0.982759,0.963636,1,0.964286,0.964286,1,0.982143,0.946429,0.982143]
unweighted_recall
0.9785714285714284 [0.982143,1,1,1,0.982143,0.982143,0.964286,0.982143,0.946429,0.946429]
usercpu_time_millis
5506.577666001249
usercpu_time_millis
3644.0831380004965
usercpu_time_millis
4117.592250999223
usercpu_time_millis
3808.6286460002157
usercpu_time_millis
5812.15467200127
usercpu_time_millis
5246.690866999415
usercpu_time_millis
5927.674372002002
usercpu_time_millis
4262.740952999593
usercpu_time_millis
5132.206864998807
usercpu_time_millis
6132.546373000878
usercpu_time_millis_testing
5.327000000761473
usercpu_time_millis_testing
5.1069000001007225
usercpu_time_millis_testing
3.982000000178232
usercpu_time_millis_testing
4.845699999350472
usercpu_time_millis_testing
4.435800001374446
usercpu_time_millis_testing
4.363699999885284
usercpu_time_millis_testing
4.478201000893023
usercpu_time_millis_testing
4.685500000050524
usercpu_time_millis_testing
4.41809999938414
usercpu_time_millis_testing
4.59930000033637
usercpu_time_millis_training
5501.250666000487
usercpu_time_millis_training
3638.976238000396
usercpu_time_millis_training
4113.610250999045
usercpu_time_millis_training
3803.782946000865
usercpu_time_millis_training
5807.718871999896
usercpu_time_millis_training
5242.32716699953
usercpu_time_millis_training
5923.196171001109
usercpu_time_millis_training
4258.0554529995425
usercpu_time_millis_training
5127.788764999423
usercpu_time_millis_training
6127.947073000541
wall_clock_time_millis
5509.066581726074
wall_clock_time_millis
3651.7794132232666
wall_clock_time_millis
4120.997428894043
wall_clock_time_millis
3809.2925548553467
wall_clock_time_millis
5827.622652053833
wall_clock_time_millis
5251.644849777222
wall_clock_time_millis
5935.320138931274
wall_clock_time_millis
4267.510175704956
wall_clock_time_millis
5135.741233825684
wall_clock_time_millis
6142.062187194824
wall_clock_time_millis_testing
5.32984733581543
wall_clock_time_millis_testing
5.2700042724609375
wall_clock_time_millis_testing
3.9870738983154297
wall_clock_time_millis_testing
4.851579666137695
wall_clock_time_millis_testing
4.439592361450195
wall_clock_time_millis_testing
4.367589950561523
wall_clock_time_millis_testing
4.481077194213867
wall_clock_time_millis_testing
4.688501358032227
wall_clock_time_millis_testing
4.42194938659668
wall_clock_time_millis_testing
4.602909088134766
wall_clock_time_millis_training
5503.736734390259
wall_clock_time_millis_training
3646.5094089508057
wall_clock_time_millis_training
4117.0103549957275
wall_clock_time_millis_training
3804.440975189209
wall_clock_time_millis_training
5823.183059692383
wall_clock_time_millis_training
5247.27725982666
wall_clock_time_millis_training
5930.839061737061
wall_clock_time_millis_training
4262.821674346924
wall_clock_time_millis_training
5131.319284439087
wall_clock_time_millis_training
6137.459278106689
weighted_recall
0.9750889679715302 [1,0.982456,1,0.965517,0.947368,1,0.982143,0.982143,0.981818,0.910714]
weighted_recall
0.9786476868327402 [1,0.964912,0.982143,0.965517,0.982456,1,1,0.964286,0.981818,0.946429]
weighted_recall
0.9875444839857651 [0.981818,0.982456,1,1,0.964912,1,1,1,1,0.946429]
weighted_recall
0.9750889679715302 [1,0.982456,0.964286,0.964912,1,0.964286,1,0.982456,0.963636,0.928571]
weighted_recall
0.9875444839857651 [0.963636,1,1,1,1,0.981818,0.982143,0.982456,0.981818,0.982456]
weighted_recall
0.9626334519572953 [0.981818,0.982456,0.982143,0.947368,0.964912,0.909091,0.982143,0.982456,0.909091,0.982456]
weighted_recall
0.9875444839857651 [0.982143,0.982456,1,0.982456,1,1,0.963636,0.982456,0.982143,1]
weighted_recall
0.9768683274021353 [1,0.964912,0.981818,0.947368,0.964912,0.982143,1,0.982456,0.964286,0.982143]
weighted_recall
0.9786476868327402 [1,0.982759,0.963636,1,0.964286,0.964286,1,0.982143,0.946429,0.982143]
weighted_recall
0.9786476868327402 [0.982143,1,1,1,0.982143,0.982143,0.964286,0.982143,0.946429,0.946429]