10578884
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)
8295166
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
0.9271983347357825
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
992
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
46
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
16
19038
random_state
8824
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.028574955340301196
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
22084035
description
https://api.openml.org/data/download/22084035/description.xml
-1
22084036
predictions
https://api.openml.org/data/download/22084036/predictions.arff
area_under_roc_curve
0.9340051932705726 [0.95137,0.946698,0.8943,0.941129,0.908509,0.947581,0.872655,0.967352,0.949796,0.960145]
average_cost
0
f_measure
0.9057772311347252 [0.947464,0.914729,0.874776,0.917186,0.898106,0.918969,0.886006,0.94026,0.878261,0.881385]
kappa
0.8952145675743439
kb_relative_information_score
0.9022033101042336
mean_absolute_error
0.019721571529181033
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.905693950177936 [0.944043,0.929947,0.877917,0.90035,0.876761,0.894265,0.856631,0.959364,0.911552,0.905694]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9068679192420055 [0.950909,0.9,0.871658,0.934664,0.920518,0.945076,0.917466,0.921902,0.847315,0.858347]
predictive_accuracy
0.905693950177936
prior_entropy
3.3218327251668773
relative_absolute_error
0.10956589456355836
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.13318194088764468
root_relative_squared_error
0.44394306702269615
total_cost
0
unweighted_recall
0.9056524722039917 [0.944043,0.929947,0.877917,0.90035,0.876761,0.894265,0.856631,0.959364,0.911552,0.905694]
area_under_roc_curve
0.9994156720462735 [1,0.999618,0.999929,0.999726,0.997533,1,0.999541,0.999929,0.999498,0.998412]
area_under_roc_curve
0.8496893145102866 [0.927093,0.967553,0.641675,0.849702,0.700208,0.726355,0.984331,0.903021,0.85069,0.948228]
area_under_roc_curve
0.9998381773261605 [1,1,1,0.999653,0.999965,0.999929,1,1,0.999928,0.998906]
area_under_roc_curve
0.8048820139231384 [0.861646,0.869515,0.578928,0.821522,0.950165,0.924795,0.308371,0.976238,0.834463,0.917614]
area_under_roc_curve
0.9998664829169929 [0.999785,0.999826,1,1,1,0.999892,0.999929,1,0.99939,0.999826]
area_under_roc_curve
0.8281056598619788 [0.793814,0.855029,0.840009,0.807817,0.635626,0.902349,0.82367,0.8963,0.873534,0.856036]
area_under_roc_curve
0.9998943720768487 [0.999965,1,1,0.999583,1,0.999929,1,0.999757,1,0.999718]
area_under_roc_curve
0.9996622120822635 [1,0.999722,1,0.999618,0.999861,0.999753,1,0.999792,0.999788,0.998094]
area_under_roc_curve
0.9989831460894452 [1,0.998529,0.999606,0.999722,0.999965,0.996294,1,0.999718,0.997847,0.998165]
area_under_roc_curve
0.8921781927535165 [0.967215,0.804273,0.932789,0.967605,0.847014,0.942723,0.687112,0.91045,0.951828,0.910997]
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
0.9714178525868359 [1,0.964912,0.99115,0.974359,0.955752,1,0.964286,0.982143,0.947368,0.934579]
f_measure
0.8028432740250904 [0.847458,0.938053,0.701031,0.766667,0.727273,0.745098,0.933333,0.8,0.743802,0.825688]
f_measure
0.9910532308772395 [1,1,1,0.991304,0.982456,0.982143,1,0.991304,0.990991,0.972477]
f_measure
0.7341438859151094 [0.87037,0.753846,0.565657,0.796117,0.912281,0.762887,0.318182,0.933333,0.733333,0.689655]
f_measure
0.9875404145670984 [0.990826,0.982759,1,1,0.982759,0.990826,0.981818,0.991304,0.972477,0.982456]
f_measure
0.7641380917192211 [0.811881,0.744186,0.727273,0.754717,0.594595,0.851852,0.811881,0.900901,0.68254,0.763636]
f_measure
0.9893376508512668 [0.990991,1,0.990991,0.982143,1,0.973913,1,0.982456,1,0.972973]
f_measure
0.9768295724853499 [0.99115,0.964912,1,0.963636,0.982143,0.972973,0.982143,0.974359,0.972973,0.964912]
f_measure
0.9769271162926538 [0.99115,0.982759,0.963636,0.964912,0.981818,0.981818,1,0.973451,0.972973,0.956522]
f_measure
0.8531505916860584 [0.972973,0.851485,0.781955,0.964286,0.830189,0.890909,0.72549,0.884956,0.817391,0.809917]
kappa
0.9683664315491372
kappa
0.7845145086341235
kappa
0.9901144403049396
kappa
0.7152938775940982
kappa
0.9861597782187135
kappa
0.7350735242383732
kappa
0.9881374952947509
kappa
0.9742980873077018
kappa
0.9742976352135766
kappa
0.8359112543224294
kb_relative_information_score
0.9708504979554671
kb_relative_information_score
0.8004342870669968
kb_relative_information_score
0.9895043577060595
kb_relative_information_score
0.7298624220829456
kb_relative_information_score
0.9860740838423393
kb_relative_information_score
0.7558779157037876
kb_relative_information_score
0.9883342256020522
kb_relative_information_score
0.9768534292426105
kb_relative_information_score
0.9759053231834315
kb_relative_information_score
0.8483350846537947
mean_absolute_error
0.00605936085662369
mean_absolute_error
0.04037845885577155
mean_absolute_error
0.0023376078729798384
mean_absolute_error
0.053555733521342797
mean_absolute_error
0.0031065656495160255
mean_absolute_error
0.048542257375499324
mean_absolute_error
0.002333060846202025
mean_absolute_error
0.004833900469282579
mean_absolute_error
0.0050441162842732624
mean_absolute_error
0.031024653560318378
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
0.9719869603455175 [1,0.964912,0.982456,0.966102,0.964286,1,0.964286,0.982143,0.915254,0.980392]
precision
0.8128352260775638 [0.793651,0.946429,0.829268,0.741935,0.857143,0.826087,0.875,0.724638,0.681818,0.849057]
precision
0.9911963343442666 [1,1,1,0.982759,0.982456,0.982143,1,0.982759,0.982143,1]
precision
0.7485729864840086 [0.886792,0.671233,0.651163,0.891304,0.912281,0.902439,0.4375,0.888889,0.676923,0.561798]
precision
0.9877834805714071 [1,0.966102,1,1,0.966102,1,1,0.982759,0.981481,0.982456]
precision
0.7763503497306877 [0.891304,0.666667,0.676923,0.816327,0.611111,0.867925,0.911111,0.925926,0.605634,0.792453]
precision
0.9895946934120226 [1,1,0.982143,1,1,0.949153,1,0.982456,1,0.981818]
precision
0.9774106831632456 [0.982456,0.964912,1,1,1,0.981818,0.964912,0.95,0.981818,0.948276]
precision
0.9772915295218398 [0.982456,0.982759,0.963636,0.964912,1,1,1,0.964912,0.981818,0.932203]
precision
0.8639765765450536 [0.981818,0.977273,0.675325,0.981818,0.88,0.907407,0.804348,0.877193,0.79661,0.753846]
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.806049822064057
predictive_accuracy
0.9911032028469751
predictive_accuracy
0.7437722419928825
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.7615658362989324
predictive_accuracy
0.98932384341637
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.8523131672597865
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
0.03366371876980168
relative_absolute_error
0.2243287890327273
relative_absolute_error
0.012986915630939101
relative_absolute_error
0.2975365547122859
relative_absolute_error
0.017258995030925386
relative_absolute_error
0.2696838481311876
relative_absolute_error
0.012961622109571596
relative_absolute_error
0.026855360973597225
relative_absolute_error
0.028023192992356824
relative_absolute_error
0.17236033646176696
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
0.07188780783037478
root_mean_squared_error
0.19044509849244218
root_mean_squared_error
0.04098224477240845
root_mean_squared_error
0.2225828419615321
root_mean_squared_error
0.047724788775295214
root_mean_squared_error
0.21100320015873286
root_mean_squared_error
0.045950027990710136
root_mean_squared_error
0.06457099875598045
root_mean_squared_error
0.06550692377893633
root_mean_squared_error
0.1653555365046616
root_relative_squared_error
0.2396285621374247
root_relative_squared_error
0.63482371343895
root_relative_squared_error
0.13660864049397575
root_relative_squared_error
0.741949095431734
root_relative_squared_error
0.15908420113920438
root_relative_squared_error
0.7033509502391719
root_relative_squared_error
0.15316768173173087
root_relative_squared_error
0.2152379578213866
root_relative_squared_error
0.21835734326973275
root_relative_squared_error
0.5511847611084403
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
0.9716143218547936 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.982143,0.981818,0.892857]
unweighted_recall
0.8063922541463378 [0.909091,0.929825,0.607143,0.793103,0.631579,0.678571,1,0.892857,0.818182,0.803571]
unweighted_recall
0.9911027568922306 [1,1,1,1,0.982456,0.982143,1,1,1,0.946429]
unweighted_recall
0.7431801093643198 [0.854545,0.859649,0.5,0.719298,0.912281,0.660714,0.25,0.982456,0.8,0.892857]
unweighted_recall
0.9874014581909318 [0.981818,1,1,1,1,0.981818,0.964286,1,0.963636,0.982456]
unweighted_recall
0.7618335611756664 [0.745455,0.842105,0.785714,0.701754,0.578947,0.836364,0.732143,0.877193,0.781818,0.736842]
unweighted_recall
0.9893796992481201 [0.982143,1,1,0.964912,1,1,1,0.982456,1,0.964286]
unweighted_recall
0.9770363408521303 [1,0.964912,1,0.929825,0.964912,0.964286,1,1,0.964286,0.982143]
unweighted_recall
0.9768450122170631 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.964286,0.982143]
unweighted_recall
0.8523182957393484 [0.964286,0.754386,0.928571,0.947368,0.785714,0.875,0.660714,0.892857,0.839286,0.875]
usercpu_time_millis
6923.430383998493
usercpu_time_millis
2866.04233899925
usercpu_time_millis
8373.666801999207
usercpu_time_millis
2896.291035001923
usercpu_time_millis
8278.308503999142
usercpu_time_millis
2878.303940000478
usercpu_time_millis
14888.330590001715
usercpu_time_millis
10640.188034001767
usercpu_time_millis
8060.975000998951
usercpu_time_millis
2897.5365350015636
usercpu_time_millis_testing
5.859599999894272
usercpu_time_millis_testing
4.133799999181065
usercpu_time_millis_testing
5.093299998407019
usercpu_time_millis_testing
4.114000001209206
usercpu_time_millis_testing
5.163499999980559
usercpu_time_millis_testing
4.212200999972993
usercpu_time_millis_testing
8.140501000525546
usercpu_time_millis_testing
6.016900000759051
usercpu_time_millis_testing
5.18489999922167
usercpu_time_millis_testing
3.7295000001904555
usercpu_time_millis_training
6917.570783998599
usercpu_time_millis_training
2861.908539000069
usercpu_time_millis_training
8368.5735020008
usercpu_time_millis_training
2892.1770350007137
usercpu_time_millis_training
8273.145003999161
usercpu_time_millis_training
2874.091739000505
usercpu_time_millis_training
14880.19008900119
usercpu_time_millis_training
10634.171134001008
usercpu_time_millis_training
8055.7901009997295
usercpu_time_millis_training
2893.807035001373
wall_clock_time_millis
6923.692464828491
wall_clock_time_millis
2866.337776184082
wall_clock_time_millis
8387.866020202637
wall_clock_time_millis
2903.9599895477295
wall_clock_time_millis
8281.589984893799
wall_clock_time_millis
2881.2882900238037
wall_clock_time_millis
14904.705047607422
wall_clock_time_millis
10656.584978103638
wall_clock_time_millis
8071.241617202759
wall_clock_time_millis
2900.615453720093
wall_clock_time_millis_testing
5.863428115844727
wall_clock_time_millis_testing
4.137516021728516
wall_clock_time_millis_testing
5.096435546875
wall_clock_time_millis_testing
4.118204116821289
wall_clock_time_millis_testing
5.166292190551758
wall_clock_time_millis_testing
4.358053207397461
wall_clock_time_millis_testing
8.143186569213867
wall_clock_time_millis_testing
6.019353866577148
wall_clock_time_millis_testing
5.188226699829102
wall_clock_time_millis_testing
3.7326812744140625
wall_clock_time_millis_training
6917.8290367126465
wall_clock_time_millis_training
2862.2002601623535
wall_clock_time_millis_training
8382.769584655762
wall_clock_time_millis_training
2899.841785430908
wall_clock_time_millis_training
8276.423692703247
wall_clock_time_millis_training
2876.9302368164062
wall_clock_time_millis_training
14896.561861038208
wall_clock_time_millis_training
10650.56562423706
wall_clock_time_millis_training
8066.05339050293
wall_clock_time_millis_training
2896.8827724456787
weighted_recall
0.9715302491103203 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.982143,0.981818,0.892857]
weighted_recall
0.806049822064057 [0.909091,0.929825,0.607143,0.793103,0.631579,0.678571,1,0.892857,0.818182,0.803571]
weighted_recall
0.9911032028469751 [1,1,1,1,0.982456,0.982143,1,1,1,0.946429]
weighted_recall
0.7437722419928826 [0.854545,0.859649,0.5,0.719298,0.912281,0.660714,0.25,0.982456,0.8,0.892857]
weighted_recall
0.9875444839857651 [0.981818,1,1,1,1,0.981818,0.964286,1,0.963636,0.982456]
weighted_recall
0.7615658362989324 [0.745455,0.842105,0.785714,0.701754,0.578947,0.836364,0.732143,0.877193,0.781818,0.736842]
weighted_recall
0.9893238434163701 [0.982143,1,1,0.964912,1,1,1,0.982456,1,0.964286]
weighted_recall
0.9768683274021353 [1,0.964912,1,0.929825,0.964912,0.964286,1,1,0.964286,0.982143]
weighted_recall
0.9768683274021353 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.964286,0.982143]
weighted_recall
0.8523131672597865 [0.964286,0.754386,0.928571,0.947368,0.785714,0.875,0.660714,0.892857,0.839286,0.875]