10578931
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)
8295213
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
0.10876026493456056
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1921
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
115
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
10
19038
random_state
21429
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.061550090691122265
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
22084129
description
https://api.openml.org/data/download/22084129/description.xml
-1
22084130
predictions
https://api.openml.org/data/download/22084130/predictions.arff
area_under_roc_curve
0.999622067594544 [0.999969,0.999647,0.99994,0.999576,0.999717,0.999646,0.999697,0.99987,0.999404,0.998759]
average_cost
0
f_measure
0.9795487488028111 [0.993677,0.97747,0.990991,0.975352,0.978947,0.981132,0.987433,0.981432,0.972047,0.957371]
kappa
0.977263335881988
kb_relative_information_score
0.9750663997958736
mean_absolute_error
0.00694783333457751
mean_prior_absolute_error
0.17999735782507298
weighted_recall
0.9795373665480427 [0.99278,0.987741,0.987433,0.968531,0.982394,0.978495,0.985663,0.980565,0.972924,0.959075]
number_of_instances
5620 [554,571,557,572,568,558,558,566,554,562]
precision
0.9795995666874375 [0.994575,0.96741,0.994575,0.98227,0.975524,0.983784,0.989209,0.982301,0.971171,0.955674]
predictive_accuracy
0.9795373665480427
prior_entropy
3.3218327251668773
relative_absolute_error
0.038599640675446086
root_mean_prior_squared_error
0.2999977942685968
root_mean_squared_error
0.056390333090331354
root_relative_squared_error
0.18796915899936065
total_cost
0
unweighted_recall
0.9795601096710882 [0.99278,0.987741,0.987433,0.968531,0.982394,0.978495,0.985663,0.980565,0.972924,0.959075]
area_under_roc_curve
0.999595230793811 [1,0.999861,0.999965,0.999932,0.998159,1,0.999682,0.999894,0.999713,0.998765]
area_under_roc_curve
0.9998204129019379 [1,1,1,0.999282,0.999931,0.999894,1,0.999965,0.999677,0.999471]
area_under_roc_curve
0.9998487338514094 [1,1,0.999965,0.999687,0.999965,1,1,1,0.999928,0.998941]
area_under_roc_curve
0.9995846744337038 [1,0.999618,0.999718,0.998402,1,1,1,0.999965,0.999857,0.998306]
area_under_roc_curve
0.9997994811232128 [0.999785,0.999965,1,1,0.999965,0.999713,0.999929,1,0.999713,0.998923]
area_under_roc_curve
0.9994198623705457 [0.999964,0.999896,1,0.999653,0.999409,0.998781,0.999506,0.999826,0.998315,0.998819]
area_under_roc_curve
0.9998030051291461 [0.999894,0.999861,1,0.999965,1,0.999824,0.999892,0.999722,0.999894,0.998977]
area_under_roc_curve
0.9996972728098256 [1,0.999305,0.999964,0.999687,0.999826,0.999647,1,0.999618,0.999894,0.999047]
area_under_roc_curve
0.9990605655813073 [1,0.998837,0.999713,0.999479,1,0.998447,1,0.999753,0.997741,0.996647]
area_under_roc_curve
0.9996482783045442 [0.999894,0.999687,1,0.999965,1,0.999894,0.998518,1,0.999259,0.999259]
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
0.9786298117049472 [1,0.973913,0.982143,0.982759,0.964286,1,0.973451,0.982143,0.964286,0.963636]
f_measure
0.9822358075406401 [1,0.99115,1,0.973913,0.973913,0.973913,1,0.981818,0.981818,0.946429]
f_measure
0.9875246330524625 [1,0.991304,0.990991,0.973913,0.982456,1,1,0.982759,0.981818,0.972477]
f_measure
0.9804862978346788 [1,0.965517,0.981818,0.964286,1,1,0.99115,0.982143,0.972973,0.947368]
f_measure
0.9802899459336928 [0.990826,0.982759,1,0.991304,0.974359,0.981818,0.972477,0.991304,0.972973,0.945455]
f_measure
0.9716659580166979 [0.981818,0.974359,0.990991,0.982143,0.948276,0.962264,0.990991,0.973451,0.963636,0.949153]
f_measure
0.9822036031487401 [0.990991,0.991304,0.990991,0.972973,1,0.964912,0.981818,0.973913,0.982143,0.972973]
f_measure
0.9732588594621064 [0.99115,0.973451,0.981818,0.954955,0.973451,0.972973,0.982143,0.956522,0.982143,0.964912]
f_measure
0.9787801275770488 [1,0.974359,0.990826,0.973913,0.990991,0.972477,1,0.990991,0.946429,0.948276]
f_measure
0.9804665128147689 [0.982143,0.957265,1,0.982456,0.982456,0.982143,0.981818,1,0.972477,0.964286]
kappa
0.9762748236618529
kappa
0.9802289501642896
kappa
0.986160070360598
kappa
0.9782520747070432
kappa
0.9782514626260779
kappa
0.9683649847665018
kappa
0.9802290892716424
kappa
0.9703440512207134
kappa
0.9762744063324538
kappa
0.9782519216900318
kb_relative_information_score
0.9731964415804311
kb_relative_information_score
0.981312141060449
kb_relative_information_score
0.9810167672132343
kb_relative_information_score
0.9759972514579246
kb_relative_information_score
0.9772264545714975
kb_relative_information_score
0.9649141657101571
kb_relative_information_score
0.9779576303628525
kb_relative_information_score
0.9707967694286785
kb_relative_information_score
0.970419205362371
kb_relative_information_score
0.977827154670136
mean_absolute_error
0.007258409757853911
mean_absolute_error
0.0057166761962944655
mean_absolute_error
0.005970962293469847
mean_absolute_error
0.007037210199498038
mean_absolute_error
0.006053742526168216
mean_absolute_error
0.009345637721918964
mean_absolute_error
0.006392710444380732
mean_absolute_error
0.007779764756010059
mean_absolute_error
0.007904685884340887
mean_absolute_error
0.006018533565840004
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
0.978828172530984 [1,0.965517,0.982143,0.982759,0.981818,1,0.964912,0.982143,0.947368,0.981481]
precision
0.9825079737933325 [1,1,1,0.982456,0.965517,0.949153,1,1,0.981818,0.946429]
precision
0.9877571543560507 [1,0.982759,1,0.965517,0.982456,1,1,0.966102,0.981818,1]
precision
0.9808834883607416 [1,0.949153,1,0.981818,1,1,0.982456,1,0.964286,0.931034]
precision
0.9808051992106606 [1,0.966102,1,0.982759,0.95,0.981818,1,0.982759,0.964286,0.981132]
precision
0.9725900443593253 [0.981818,0.95,1,1,0.932203,1,1,0.982143,0.963636,0.918033]
precision
0.9824819354777019 [1,0.982759,0.982143,1,1,0.948276,0.981818,0.965517,0.982143,0.981818]
precision
0.9735470463569165 [0.982456,0.982143,0.981818,0.981481,0.982143,0.981818,0.964912,0.948276,0.982143,0.948276]
precision
0.9793624811335209 [1,0.966102,1,0.965517,1,1,1,1,0.946429,0.916667]
precision
0.9809056325929563 [0.982143,0.933333,1,0.982456,0.965517,0.982143,1,1,1,0.964286]
predictive_accuracy
0.9786476868327402
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9875444839857651
predictive_accuracy
0.9804270462633453
predictive_accuracy
0.9804270462633453
predictive_accuracy
0.9715302491103204
predictive_accuracy
0.9822064056939501
predictive_accuracy
0.9733096085409252
predictive_accuracy
0.9786476868327402
predictive_accuracy
0.9804270462633453
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
0.04032522085844691
relative_absolute_error
0.031759881004563194
relative_absolute_error
0.03317253694990458
relative_absolute_error
0.039096230036890105
relative_absolute_error
0.033632481642200666
relative_absolute_error
0.05192110298024983
relative_absolute_error
0.035515531954883064
relative_absolute_error
0.04322149207249351
relative_absolute_error
0.04391543049304591
relative_absolute_error
0.03343652068177924
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
0.06012328650533868
root_mean_squared_error
0.047457532981345626
root_mean_squared_error
0.04548326718018122
root_mean_squared_error
0.05434625087905793
root_mean_squared_error
0.054289488699529376
root_mean_squared_error
0.0695363194404005
root_mean_squared_error
0.05090874700267288
root_mean_squared_error
0.06149623564289282
root_mean_squared_error
0.06284451154426508
root_mean_squared_error
0.05295147410671372
root_relative_squared_error
0.20041307602877317
root_relative_squared_error
0.15819345079687033
root_relative_squared_error
0.151612175692534
root_relative_squared_error
0.1811557051050314
root_relative_squared_error
0.18096675043832228
root_relative_squared_error
0.2317900217520284
root_relative_squared_error
0.1696968445773976
root_relative_squared_error
0.20498868576433615
root_relative_squared_error
0.20948259799527094
root_relative_squared_error
0.17650479822322712
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
0.9787258506768488 [1,0.982456,0.982143,0.982759,0.947368,1,0.982143,0.982143,0.981818,0.946429]
unweighted_recall
0.9822961989613532 [1,0.982456,1,0.965517,0.982456,1,1,0.964286,0.981818,0.946429]
unweighted_recall
0.9875301891091365 [1,1,0.982143,0.982456,0.982456,1,1,1,0.981818,0.946429]
unweighted_recall
0.9805126452494873 [1,0.982456,0.964286,0.947368,1,1,1,0.964912,0.981818,0.964286]
unweighted_recall
0.9804163818637501 [0.981818,1,1,1,1,0.981818,0.946429,1,0.981818,0.912281]
unweighted_recall
0.9714205969469125 [0.981818,1,0.982143,0.964912,0.964912,0.927273,0.982143,0.964912,0.963636,0.982456]
unweighted_recall
0.9822357028935975 [0.982143,1,1,0.947368,1,0.982143,0.981818,0.982456,0.982143,0.964286]
unweighted_recall
0.9734951013898383 [1,0.964912,0.981818,0.929825,0.964912,0.964286,1,0.964912,0.982143,0.982143]
unweighted_recall
0.9786318657144429 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.946429,0.982143]
unweighted_recall
0.9804197994987467 [0.982143,0.982456,1,0.982456,1,0.982143,0.964286,1,0.946429,0.964286]
usercpu_time_millis
16512.834606999604
usercpu_time_millis
16669.745206001608
usercpu_time_millis
16585.156608000034
usercpu_time_millis
16499.611006998748
usercpu_time_millis
16650.906307000696
usercpu_time_millis
16611.32820399871
usercpu_time_millis
16609.313601000395
usercpu_time_millis
16515.580603998387
usercpu_time_millis
16435.39989999954
usercpu_time_millis
16617.204506001144
usercpu_time_millis_testing
9.514100000160397
usercpu_time_millis_testing
8.971100000053411
usercpu_time_millis_testing
8.825099999739905
usercpu_time_millis_testing
10.102499998538406
usercpu_time_millis_testing
8.329500000400003
usercpu_time_millis_testing
9.290199999668403
usercpu_time_millis_testing
8.993400000690599
usercpu_time_millis_testing
9.967399999368354
usercpu_time_millis_testing
11.719199999788543
usercpu_time_millis_testing
10.081300000820193
usercpu_time_millis_training
16503.320506999444
usercpu_time_millis_training
16660.774106001554
usercpu_time_millis_training
16576.331508000294
usercpu_time_millis_training
16489.50850700021
usercpu_time_millis_training
16642.576807000296
usercpu_time_millis_training
16602.03800399904
usercpu_time_millis_training
16600.320200999704
usercpu_time_millis_training
16505.61320399902
usercpu_time_millis_training
16423.68069999975
usercpu_time_millis_training
16607.123206000324
wall_clock_time_millis
16513.645887374878
wall_clock_time_millis
16682.069778442383
wall_clock_time_millis
16610.095977783203
wall_clock_time_millis
16527.763843536377
wall_clock_time_millis
16713.73748779297
wall_clock_time_millis
16639.43338394165
wall_clock_time_millis
16626.285314559937
wall_clock_time_millis
16585.77036857605
wall_clock_time_millis
16451.99179649353
wall_clock_time_millis
16652.392148971558
wall_clock_time_millis_testing
9.521961212158203
wall_clock_time_millis_testing
8.974075317382812
wall_clock_time_millis_testing
8.829116821289062
wall_clock_time_millis_testing
10.113000869750977
wall_clock_time_millis_testing
8.332490921020508
wall_clock_time_millis_testing
9.293317794799805
wall_clock_time_millis_testing
8.999109268188477
wall_clock_time_millis_testing
9.969949722290039
wall_clock_time_millis_testing
11.725187301635742
wall_clock_time_millis_testing
10.087251663208008
wall_clock_time_millis_training
16504.12392616272
wall_clock_time_millis_training
16673.095703125
wall_clock_time_millis_training
16601.266860961914
wall_clock_time_millis_training
16517.650842666626
wall_clock_time_millis_training
16705.40499687195
wall_clock_time_millis_training
16630.14006614685
wall_clock_time_millis_training
16617.286205291748
wall_clock_time_millis_training
16575.80041885376
wall_clock_time_millis_training
16440.266609191895
wall_clock_time_millis_training
16642.30489730835
weighted_recall
0.9786476868327402 [1,0.982456,0.982143,0.982759,0.947368,1,0.982143,0.982143,0.981818,0.946429]
weighted_recall
0.9822064056939501 [1,0.982456,1,0.965517,0.982456,1,1,0.964286,0.981818,0.946429]
weighted_recall
0.9875444839857651 [1,1,0.982143,0.982456,0.982456,1,1,1,0.981818,0.946429]
weighted_recall
0.9804270462633452 [1,0.982456,0.964286,0.947368,1,1,1,0.964912,0.981818,0.964286]
weighted_recall
0.9804270462633452 [0.981818,1,1,1,1,0.981818,0.946429,1,0.981818,0.912281]
weighted_recall
0.9715302491103203 [0.981818,1,0.982143,0.964912,0.964912,0.927273,0.982143,0.964912,0.963636,0.982456]
weighted_recall
0.9822064056939501 [0.982143,1,1,0.947368,1,0.982143,0.981818,0.982456,0.982143,0.964286]
weighted_recall
0.9733096085409253 [1,0.964912,0.981818,0.929825,0.964912,0.964286,1,0.964912,0.982143,0.982143]
weighted_recall
0.9786476868327402 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.946429,0.982143]
weighted_recall
0.9804270462633452 [0.982143,0.982456,1,0.982456,1,0.982143,0.964286,1,0.946429,0.964286]