10578756
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)
8295038
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
0.4135186749303344
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1984
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
172
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
7
19038
random_state
34908
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.09832313171649718
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
22083779
description
https://api.openml.org/data/download/22083779/description.xml
-1
22083780
predictions
https://api.openml.org/data/download/22083780/predictions.arff
area_under_roc_curve
0.9995966511156075 [0.999954,0.999644,0.999901,0.999725,0.999554,0.999606,0.99964,0.999878,0.999219,0.998844]
average_cost
0
f_measure
0.9784911911658271 [0.99187,0.976542,0.990099,0.972735,0.98326,0.983784,0.986547,0.976211,0.972047,0.952212]
kappa
0.9760770987102347
kb_relative_information_score
0.978815545559951
mean_absolute_error
0.005315596740978068
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9784697508896797 [0.990975,0.984238,0.987433,0.966783,0.982394,0.978495,0.985663,0.978799,0.972924,0.957295]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.978546779800128 [0.992767,0.968966,0.99278,0.978761,0.984127,0.98913,0.987433,0.973638,0.971171,0.947183]
predictive_accuracy
0.9784697508896797
prior_entropy
3.3218327251668773
relative_absolute_error
0.029531526491316226
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.056338732864910784
root_relative_squared_error
0.18779715698332455
total_cost
0
unweighted_recall
0.9784999019957876 [0.990975,0.984238,0.987433,0.966783,0.982394,0.978495,0.985663,0.978799,0.972924,0.957295]
area_under_roc_curve
0.9996373733339198 [1,0.999687,1,0.999932,0.998055,1,0.999753,0.999894,0.999713,0.999365]
area_under_roc_curve
0.9999119542935526 [1,1,1,0.999624,1,0.999929,1,0.999929,0.999892,0.999753]
area_under_roc_curve
0.9997749077538021 [1,0.999931,1,0.999826,0.999931,1,1,1,0.999857,0.9982]
area_under_roc_curve
0.9996516900169526 [1,0.999653,0.999577,0.999062,1,1,1,0.999965,0.999534,0.99873]
area_under_roc_curve
0.9998663716947618 [0.999928,0.999931,1,1,1,0.999713,1,1,0.999677,0.999409]
area_under_roc_curve
0.9992404013039728 [0.999821,0.999896,0.999894,0.999409,0.999166,0.998566,0.998765,0.999826,0.998494,0.998541]
area_under_roc_curve
0.9998944347200441 [0.999929,0.999792,1,0.999896,1,0.999788,0.999964,0.999931,1,0.999647]
area_under_roc_curve
0.9993455649862456 [1,0.999062,0.999964,0.999687,0.999896,0.999647,0.999928,0.999444,0.998165,0.997671]
area_under_roc_curve
0.9993703191264455 [1,0.99935,0.99957,0.999792,1,0.998765,1,0.999929,0.998906,0.997388]
area_under_roc_curve
0.999824139152272 [0.999929,0.999896,1,0.999931,0.999965,0.999929,0.999859,1,0.999047,0.999682]
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
0.9731629772117011 [1,0.965517,0.990991,0.97479,0.955752,1,0.973451,0.972973,0.964286,0.934579]
f_measure
0.9892919371474848 [1,1,1,0.973451,0.991304,0.982456,1,0.982143,0.981818,0.982143]
f_measure
0.9822195878316559 [1,0.982456,0.990991,0.973451,0.973451,1,1,0.974359,0.981818,0.946429]
f_measure
0.9733841810470472 [0.990826,0.964912,0.981818,0.955752,0.991304,1,0.99115,0.973451,0.945455,0.93913]
f_measure
0.9857588245054935 [0.990826,0.974359,1,1,1,0.990826,0.972477,0.991304,0.973451,0.964286]
f_measure
0.9698886044271656 [0.981818,0.982759,0.981818,0.973913,0.973913,0.952381,0.990991,0.973451,0.963636,0.92437]
f_measure
0.9839698816544551 [0.990991,0.973451,0.990991,0.982456,0.991304,0.982143,0.981818,0.982456,1,0.964286]
f_measure
0.9678977359976929 [0.99115,0.973451,0.982143,0.954128,0.973451,0.954955,0.982143,0.93913,0.972973,0.956522]
f_measure
0.9751631151670039 [0.99115,0.982759,0.981818,0.955752,0.990991,0.981818,1,0.973451,0.954955,0.93913]
f_measure
0.9840258150164007 [0.982143,0.966102,1,0.982456,0.990991,0.99115,0.972973,1,0.981818,0.972973]
kappa
0.9703426949097088
kappa
0.9881374952947509
kappa
0.9802288806098791
kappa
0.9703434252464346
kappa
0.9841829931996722
kappa
0.9663874415544665
kappa
0.9822061177463897
kappa
0.9644133622266625
kappa
0.972320627605495
kappa
0.9822060551478607
kb_relative_information_score
0.9754280375812917
kb_relative_information_score
0.9873914505150718
kb_relative_information_score
0.9832127858847736
kb_relative_information_score
0.9754228507061099
kb_relative_information_score
0.9839838844937643
kb_relative_information_score
0.9686384143078268
kb_relative_information_score
0.9834177205301802
kb_relative_information_score
0.9690551620714156
kb_relative_information_score
0.9777490928814382
kb_relative_information_score
0.9838559587273101
mean_absolute_error
0.005552528263462872
mean_absolute_error
0.003409313172932004
mean_absolute_error
0.004702647123188971
mean_absolute_error
0.006701554605840424
mean_absolute_error
0.004230626021409289
mean_absolute_error
0.007312424780809065
mean_absolute_error
0.0037595844151594535
mean_absolute_error
0.00807195950128031
mean_absolute_error
0.005619198427058582
mean_absolute_error
0.0037961310986397018
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
0.9737324759011947 [1,0.949153,1,0.95082,0.964286,1,0.964912,0.981818,0.947368,0.980392]
precision
0.9894772364707326 [1,1,1,1,0.982759,0.965517,1,0.982143,0.981818,0.982143]
precision
0.9824097610574478 [1,0.982456,1,0.982143,0.982143,1,1,0.95,0.981818,0.946429]
precision
0.9737285606735296 [1,0.964912,1,0.964286,0.982759,1,0.982456,0.982143,0.945455,0.915254]
precision
0.986274110599181 [1,0.95,1,1,1,1,1,0.982759,0.948276,0.981818]
precision
0.970966941483249 [0.981818,0.966102,1,0.965517,0.965517,1,1,0.982143,0.963636,0.887097]
precision
0.9840164437354276 [1,0.982143,0.982143,0.982456,0.982759,0.982143,0.981818,0.982456,1,0.964286]
precision
0.9685764952746125 [0.982456,0.982143,0.964912,1,0.982143,0.963636,0.964912,0.931034,0.981818,0.932203]
precision
0.9755067454537457 [0.982456,0.982759,0.981818,0.964286,1,1,1,0.964912,0.963636,0.915254]
precision
0.9844189952050759 [0.982143,0.934426,1,0.982456,1,0.982456,0.981818,1,1,0.981818]
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.98932384341637
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9857651245551601
predictive_accuracy
0.9697508896797153
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9679715302491103
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9839857651245552
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
0.03084793171185081
relative_absolute_error
0.018940967961382286
relative_absolute_error
0.02612623021032253
relative_absolute_error
0.03723144727059686
relative_absolute_error
0.02350388233146846
relative_absolute_error
0.04062528116077666
relative_absolute_error
0.020886858805101174
relative_absolute_error
0.04484481787505922
relative_absolute_error
0.031218130810102433
relative_absolute_error
0.021089757928881177
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
0.06329998956767378
root_mean_squared_error
0.04255194438657118
root_mean_squared_error
0.04720013007795543
root_mean_squared_error
0.05799397970106617
root_mean_squared_error
0.047296658357234546
root_mean_squared_error
0.07152984613518433
root_mean_squared_error
0.04893590858521034
root_mean_squared_error
0.06593208442817437
root_mean_squared_error
0.05975949814112952
root_mean_squared_error
0.05162716622942935
root_relative_squared_error
0.21100219830331934
root_relative_squared_error
0.14184131575642947
root_relative_squared_error
0.15733510052698294
root_relative_squared_error
0.19331490424193976
root_relative_squared_error
0.1576570856445449
root_relative_squared_error
0.23843517639446304
root_relative_squared_error
0.16312067694382995
root_relative_squared_error
0.21977493736556372
root_relative_squared_error
0.1991991761552607
root_relative_squared_error
0.17209044152006087
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
0.9733071314650262 [1,0.982456,0.982143,1,0.947368,1,0.982143,0.964286,0.981818,0.892857]
unweighted_recall
0.9894379758172862 [1,1,1,0.948276,1,1,1,0.982143,0.981818,0.982143]
unweighted_recall
0.9822670312143996 [1,0.982456,0.982143,0.964912,0.964912,1,1,1,0.981818,0.946429]
unweighted_recall
0.9733037138300296 [0.981818,0.964912,0.964286,0.947368,1,1,1,0.964912,0.945455,0.964286]
unweighted_recall
0.9857433356117566 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.947368]
unweighted_recall
0.969571086807929 [0.981818,1,0.964286,0.982456,0.982456,0.909091,0.982143,0.964912,0.963636,0.964912]
unweighted_recall
0.9840214171793118 [0.982143,0.964912,1,0.982456,1,0.982143,0.981818,0.982456,1,0.964286]
unweighted_recall
0.968233082706767 [1,0.964912,1,0.912281,0.964912,0.946429,1,0.947368,0.964286,0.982143]
unweighted_recall
0.9751230937846183 [1,0.982759,0.981818,0.947368,0.982143,0.964286,1,0.982143,0.946429,0.964286]
unweighted_recall
0.9839598997493733 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.964286,0.964286]
usercpu_time_millis
8220.802103998722
usercpu_time_millis
8337.30650600046
usercpu_time_millis
5679.115669998282
usercpu_time_millis
5802.288273000158
usercpu_time_millis
5625.758772001063
usercpu_time_millis
8116.283099001521
usercpu_time_millis
8040.21740099779
usercpu_time_millis
4126.026950998494
usercpu_time_millis
6812.292583999806
usercpu_time_millis
9736.447425000733
usercpu_time_millis_testing
5.447699999422184
usercpu_time_millis_testing
5.759300000136136
usercpu_time_millis_testing
5.3633999996236525
usercpu_time_millis_testing
5.963800000245101
usercpu_time_millis_testing
4.912899999908404
usercpu_time_millis_testing
5.686000000423519
usercpu_time_millis_testing
6.701099999190774
usercpu_time_millis_testing
4.694200999438181
usercpu_time_millis_testing
5.37360000089393
usercpu_time_millis_testing
6.23980000091251
usercpu_time_millis_training
8215.3544039993
usercpu_time_millis_training
8331.547206000323
usercpu_time_millis_training
5673.752269998658
usercpu_time_millis_training
5796.324472999913
usercpu_time_millis_training
5620.845872001155
usercpu_time_millis_training
8110.597099001097
usercpu_time_millis_training
8033.516300998599
usercpu_time_millis_training
4121.3327499990555
usercpu_time_millis_training
6806.918983998912
usercpu_time_millis_training
9730.20762499982
wall_clock_time_millis
8226.499557495117
wall_clock_time_millis
8342.768669128418
wall_clock_time_millis
5683.728456497192
wall_clock_time_millis
5822.530031204224
wall_clock_time_millis
5645.063877105713
wall_clock_time_millis
8131.55460357666
wall_clock_time_millis
8044.487953186035
wall_clock_time_millis
4131.649732589722
wall_clock_time_millis
6815.8416748046875
wall_clock_time_millis
9739.264011383057
wall_clock_time_millis_testing
5.450248718261719
wall_clock_time_millis_testing
5.762815475463867
wall_clock_time_millis_testing
5.369424819946289
wall_clock_time_millis_testing
5.967617034912109
wall_clock_time_millis_testing
5.03087043762207
wall_clock_time_millis_testing
5.692720413208008
wall_clock_time_millis_testing
6.704807281494141
wall_clock_time_millis_testing
4.697084426879883
wall_clock_time_millis_testing
5.377769470214844
wall_clock_time_millis_testing
6.244421005249023
wall_clock_time_millis_training
8221.049308776855
wall_clock_time_millis_training
8337.005853652954
wall_clock_time_millis_training
5678.359031677246
wall_clock_time_millis_training
5816.5624141693115
wall_clock_time_millis_training
5640.033006668091
wall_clock_time_millis_training
8125.861883163452
wall_clock_time_millis_training
8037.783145904541
wall_clock_time_millis_training
4126.952648162842
wall_clock_time_millis_training
6810.463905334473
wall_clock_time_millis_training
9733.019590377808
weighted_recall
0.9733096085409253 [1,0.982456,0.982143,1,0.947368,1,0.982143,0.964286,0.981818,0.892857]
weighted_recall
0.9893238434163701 [1,1,1,0.948276,1,1,1,0.982143,0.981818,0.982143]
weighted_recall
0.9822064056939501 [1,0.982456,0.982143,0.964912,0.964912,1,1,1,0.981818,0.946429]
weighted_recall
0.9733096085409253 [0.981818,0.964912,0.964286,0.947368,1,1,1,0.964912,0.945455,0.964286]
weighted_recall
0.9857651245551602 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.947368]
weighted_recall
0.9697508896797153 [0.981818,1,0.964286,0.982456,0.982456,0.909091,0.982143,0.964912,0.963636,0.964912]
weighted_recall
0.9839857651245552 [0.982143,0.964912,1,0.982456,1,0.982143,0.981818,0.982456,1,0.964286]
weighted_recall
0.9679715302491103 [1,0.964912,1,0.912281,0.964912,0.946429,1,0.947368,0.964286,0.982143]
weighted_recall
0.9750889679715302 [1,0.982759,0.981818,0.947368,0.982143,0.964286,1,0.982143,0.946429,0.964286]
weighted_recall
0.9839857651245552 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.964286,0.964286]