10578752
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)
8295034
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
"most_frequent"
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
0.23364904416188356
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
978
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
134
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
6
19038
random_state
2443
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.019233158853162298
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
22083771
description
https://api.openml.org/data/download/22083771/description.xml
-1
22083772
predictions
https://api.openml.org/data/download/22083772/predictions.arff
area_under_roc_curve
0.9996881674587158 [0.999978,0.999676,0.999938,0.999643,0.999748,0.99968,0.999899,0.999885,0.999441,0.998997]
average_cost
0
f_measure
0.9793690373477639 [0.991855,0.976542,0.990081,0.978089,0.980634,0.983842,0.986571,0.981498,0.969314,0.955516]
kappa
0.9770656031680932
kb_relative_information_score
0.9755604599145881
mean_absolute_error
0.006644094569059755
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9793594306049822 [0.98917,0.984238,0.985637,0.975524,0.980634,0.982079,0.987455,0.984099,0.969314,0.955516]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9793997525254327 [0.994555,0.968966,0.994565,0.980668,0.980634,0.985612,0.985689,0.97891,0.969314,0.955516]
predictive_accuracy
0.9793594306049822
prior_entropy
3.3218327251668773
relative_absolute_error
0.03691217831939896
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.05641050154102081
root_relative_squared_error
0.18803638766262007
total_cost
0
unweighted_recall
0.9793666558739842 [0.98917,0.984238,0.985637,0.975524,0.980634,0.982079,0.987455,0.984099,0.969314,0.955516]
area_under_roc_curve
0.9997958953252981 [1,0.999792,1,0.999932,0.999375,1,0.999788,0.999859,0.999749,0.999471]
area_under_roc_curve
0.9998802985620501 [1,1,1,0.999589,0.999965,0.999965,1,0.999894,0.999821,0.999577]
area_under_roc_curve
0.9997643789723057 [1,0.999965,1,0.999722,0.999965,1,1,1,0.999713,0.998271]
area_under_roc_curve
0.9997078153258527 [1,0.999757,0.999788,0.998576,1,1,1,0.999965,0.999857,0.999153]
area_under_roc_curve
0.9998487473661878 [0.999857,0.999861,1,1,1,0.999964,0.999894,1,0.99957,0.99934]
area_under_roc_curve
0.9991316037944575 [0.999928,0.999826,1,0.999722,0.998958,0.997418,0.999647,0.999896,0.99792,0.99795]
area_under_roc_curve
0.9998627929704577 [0.999965,0.999861,1,0.999792,1,0.999824,0.999928,0.999965,1,0.999294]
area_under_roc_curve
0.9997078084448527 [1,0.99927,0.999964,0.999653,0.999896,0.999753,1,0.999548,0.999753,0.999259]
area_under_roc_curve
0.9993913348262612 [1,0.999282,0.999821,0.999757,1,0.999224,1,0.999824,0.998377,0.997636]
area_under_roc_curve
0.9998839269661145 [0.999965,0.999861,1,1,0.999894,0.999965,0.999753,1,0.999612,0.999788]
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
0.9750168226847596 [1,0.964912,0.990991,0.991453,0.955752,1,0.973451,0.973451,0.955752,0.944444]
f_measure
0.985747200844913 [1,0.99115,1,0.973913,0.991304,0.982456,1,0.972477,0.972973,0.973451]
f_measure
0.9875100207467798 [0.990826,0.991304,0.990991,0.973913,0.991304,1,1,0.991304,0.981818,0.963636]
f_measure
0.9822029874520978 [1,0.974359,0.981818,0.964286,1,1,0.99115,0.99115,0.972973,0.946429]
f_measure
0.9785757128162142 [0.981481,0.974359,1,0.991304,0.982759,0.981818,0.972477,0.991304,0.954955,0.954955]
f_measure
0.9680851515929424 [0.990826,0.974359,0.990991,0.982143,0.947368,0.952381,0.973451,0.982456,0.954955,0.932203]
f_measure
0.9839857651245552 [0.990991,0.973451,0.990991,0.982456,1,0.973451,0.990991,0.982456,0.990991,0.964286]
f_measure
0.9733310405880372 [0.99115,0.982143,0.981818,0.954955,0.972973,0.973451,0.990991,0.957265,0.972973,0.956522]
f_measure
0.9769559350786322 [0.99115,0.982759,0.972477,0.973913,0.990991,0.981818,1,0.973451,0.963636,0.93913]
f_measure
0.9822298394481649 [0.982143,0.957265,1,0.991304,0.973451,0.99115,0.972973,1,0.972477,0.981818]
kappa
0.9723205302300055
kappa
0.9841832157745687
kappa
0.9861600216711405
kappa
0.9802290197182107
kappa
0.976274155927767
kappa
0.9644106078623145
kappa
0.9822062429421263
kappa
0.9703440512207134
kappa
0.9742974543714732
kappa
0.9802289501642896
kb_relative_information_score
0.9771430417950016
kb_relative_information_score
0.9814697894224638
kb_relative_information_score
0.9810154659347781
kb_relative_information_score
0.9775098803842268
kb_relative_information_score
0.9767364364775372
kb_relative_information_score
0.9580254721919349
kb_relative_information_score
0.9790101173006474
kb_relative_information_score
0.9712837425396252
kb_relative_information_score
0.9727646155319838
kb_relative_information_score
0.9806458809393813
mean_absolute_error
0.0057723820372235475
mean_absolute_error
0.005482818375014947
mean_absolute_error
0.005969923847846652
mean_absolute_error
0.006686955508011911
mean_absolute_error
0.006418585336323033
mean_absolute_error
0.01104320413196624
mean_absolute_error
0.006145737519694418
mean_absolute_error
0.007253311524569541
mean_absolute_error
0.006797232316605085
mean_absolute_error
0.004870795093342195
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
0.9754117149114334 [1,0.964912,1,0.983051,0.964286,1,0.964912,0.964912,0.931034,0.980769]
precision
0.9860132829927316 [1,1,1,0.982456,0.982759,0.965517,1,1,0.964286,0.964912]
precision
0.9876319748389941 [1,0.982759,1,0.965517,0.982759,1,1,0.982759,0.981818,0.981481]
precision
0.9825033710124552 [1,0.95,1,0.981818,1,1,0.982456,1,0.964286,0.946429]
precision
0.9790930520316834 [1,0.95,1,0.982759,0.966102,0.981818,1,0.982759,0.946429,0.981481]
precision
0.9690962664961218 [1,0.95,1,1,0.947368,1,0.964912,0.982456,0.946429,0.901639]
precision
0.9840799730643335 [1,0.982143,0.982143,0.982456,1,0.964912,0.982143,0.982456,1,0.964286]
precision
0.9740216035205972 [0.982456,1,0.981818,0.981481,1,0.964912,0.982143,0.933333,0.981818,0.932203]
precision
0.9773768613347833 [0.982456,0.982759,0.981481,0.965517,1,1,1,0.964912,0.981481,0.915254]
precision
0.9826542546976439 [0.982143,0.933333,1,0.982759,0.964912,0.982456,0.981818,1,1,1]
predictive_accuracy
0.9750889679715303
predictive_accuracy
0.9857651245551601
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9786476868327402
predictive_accuracy
0.9679715302491103
predictive_accuracy
0.9839857651245552
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9768683274021351
predictive_accuracy
0.9822064056939501
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
0.0320693634412829
relative_absolute_error
0.03046064761775036
relative_absolute_error
0.03316676771638529
relative_absolute_error
0.03715033988985167
relative_absolute_error
0.03565942102090391
relative_absolute_error
0.06135218976260583
relative_absolute_error
0.034143441841463666
relative_absolute_error
0.04029671286864074
relative_absolute_error
0.03776283937307219
relative_absolute_error
0.027060153290432716
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
0.058680656336650344
root_mean_squared_error
0.04775108114598012
root_mean_squared_error
0.04633451199518518
root_mean_squared_error
0.05217367256533184
root_mean_squared_error
0.05332629686282944
root_mean_squared_error
0.07404719665425549
root_mean_squared_error
0.049038012290332625
root_mean_squared_error
0.06296528637599091
root_mean_squared_error
0.062330206801794054
root_mean_squared_error
0.051456706699810895
root_relative_squared_error
0.1956042579071447
root_relative_squared_error
0.15917195503468798
root_relative_squared_error
0.15444968246042898
root_relative_squared_error
0.17391371600821565
root_relative_squared_error
0.17775607925847348
root_relative_squared_error
0.24682642770412
root_relative_squared_error
0.16346102467578266
root_relative_squared_error
0.20988555101065168
root_relative_squared_error
0.20776824154684448
root_relative_squared_error
0.17152224345970285
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
0.9751241740715425 [1,0.964912,0.982143,1,0.947368,1,0.982143,0.982143,0.981818,0.910714]
unweighted_recall
0.9858362992119799 [1,0.982456,1,0.965517,1,1,1,0.946429,0.981818,0.982143]
unweighted_recall
0.987466393255867 [0.981818,1,0.982143,0.982456,1,1,1,1,0.981818,0.946429]
unweighted_recall
0.9822357028935975 [1,1,0.964286,0.947368,1,1,1,0.982456,0.981818,0.946429]
unweighted_recall
0.9785344041922988 [0.963636,1,1,1,1,0.981818,0.946429,1,0.963636,0.929825]
unweighted_recall
0.9678480291638186 [0.981818,1,0.982143,0.964912,0.947368,0.909091,0.982143,0.982456,0.963636,0.964912]
unweighted_recall
0.9840538847117793 [0.982143,0.964912,1,0.982456,1,0.982143,1,0.982456,0.982143,0.964286]
unweighted_recall
0.9734951013898382 [1,0.964912,0.981818,0.929825,0.947368,0.982143,1,0.982456,0.964286,0.982143]
unweighted_recall
0.976813683896261 [1,0.982759,0.963636,0.982456,0.982143,0.964286,1,0.982143,0.946429,0.964286]
unweighted_recall
0.982174185463659 [0.982143,0.982456,1,1,0.982143,1,0.964286,1,0.946429,0.964286]
usercpu_time_millis
10785.197134000555
usercpu_time_millis
8483.591703999991
usercpu_time_millis
7430.641793000177
usercpu_time_millis
8186.00690400126
usercpu_time_millis
7220.2861919995485
usercpu_time_millis
6378.175478999765
usercpu_time_millis
7906.53669600033
usercpu_time_millis
8810.694509000314
usercpu_time_millis
8934.460710999701
usercpu_time_millis
9786.733120998178
usercpu_time_millis_testing
6.191200000102981
usercpu_time_millis_testing
5.377900000894442
usercpu_time_millis_testing
5.009399999835296
usercpu_time_millis_testing
5.43400000060501
usercpu_time_millis_testing
5.386700000599376
usercpu_time_millis_testing
5.585900000369293
usercpu_time_millis_testing
5.316200000379467
usercpu_time_millis_testing
5.491300000358024
usercpu_time_millis_testing
5.445500000860193
usercpu_time_millis_testing
6.043900999429752
usercpu_time_millis_training
10779.005934000452
usercpu_time_millis_training
8478.213803999097
usercpu_time_millis_training
7425.632393000342
usercpu_time_millis_training
8180.572904000655
usercpu_time_millis_training
7214.899491998949
usercpu_time_millis_training
6372.589578999396
usercpu_time_millis_training
7901.220495999951
usercpu_time_millis_training
8805.203208999956
usercpu_time_millis_training
8929.015210998841
usercpu_time_millis_training
9780.689219998749
wall_clock_time_millis
10834.322452545166
wall_clock_time_millis
8485.992908477783
wall_clock_time_millis
7432.092666625977
wall_clock_time_millis
8189.515590667725
wall_clock_time_millis
7228.601694107056
wall_clock_time_millis
6387.298822402954
wall_clock_time_millis
7928.473234176636
wall_clock_time_millis
8814.197778701782
wall_clock_time_millis
8942.626237869263
wall_clock_time_millis
9796.382427215576
wall_clock_time_millis_testing
6.193876266479492
wall_clock_time_millis_testing
5.383014678955078
wall_clock_time_millis_testing
5.017757415771484
wall_clock_time_millis_testing
5.436897277832031
wall_clock_time_millis_testing
5.395650863647461
wall_clock_time_millis_testing
5.589962005615234
wall_clock_time_millis_testing
5.318164825439453
wall_clock_time_millis_testing
5.49769401550293
wall_clock_time_millis_testing
5.859375
wall_clock_time_millis_testing
6.04701042175293
wall_clock_time_millis_training
10828.128576278687
wall_clock_time_millis_training
8480.609893798828
wall_clock_time_millis_training
7427.074909210205
wall_clock_time_millis_training
8184.078693389893
wall_clock_time_millis_training
7223.206043243408
wall_clock_time_millis_training
6381.708860397339
wall_clock_time_millis_training
7923.155069351196
wall_clock_time_millis_training
8808.70008468628
wall_clock_time_millis_training
8936.766862869263
wall_clock_time_millis_training
9790.335416793823
weighted_recall
0.9750889679715302 [1,0.964912,0.982143,1,0.947368,1,0.982143,0.982143,0.981818,0.910714]
weighted_recall
0.9857651245551602 [1,0.982456,1,0.965517,1,1,1,0.946429,0.981818,0.982143]
weighted_recall
0.9875444839857651 [0.981818,1,0.982143,0.982456,1,1,1,1,0.981818,0.946429]
weighted_recall
0.9822064056939501 [1,1,0.964286,0.947368,1,1,1,0.982456,0.981818,0.946429]
weighted_recall
0.9786476868327402 [0.963636,1,1,1,1,0.981818,0.946429,1,0.963636,0.929825]
weighted_recall
0.9679715302491103 [0.981818,1,0.982143,0.964912,0.947368,0.909091,0.982143,0.982456,0.963636,0.964912]
weighted_recall
0.9839857651245552 [0.982143,0.964912,1,0.982456,1,0.982143,1,0.982456,0.982143,0.964286]
weighted_recall
0.9733096085409253 [1,0.964912,0.981818,0.929825,0.947368,0.982143,1,0.982456,0.964286,0.982143]
weighted_recall
0.9768683274021353 [1,0.982759,0.963636,0.982456,0.982143,0.964286,1,0.982143,0.946429,0.964286]
weighted_recall
0.9822064056939501 [0.982143,0.982456,1,1,0.982143,1,0.964286,1,0.946429,0.964286]