10576288
28997
Marc Boel
16
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)
8292570
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
"mean"
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
0.3769214775400738
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
540
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
177
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
21971
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.2962205297286032
19038
verbose
0
19038
warm_start
false
19038
openml-python
Sklearn_0.24.2.
16
mfeat-karhunen
https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff
-1
22078843
description
https://api.openml.org/data/download/22078843/description.xml
-1
22078844
predictions
https://api.openml.org/data/download/22078844/predictions.arff
area_under_roc_curve
0.9971891666666667 [0.998878,0.997672,0.999847,0.995075,0.998108,0.994781,0.993575,0.999392,0.997353,0.997211]
average_cost
0
f_measure
0.9500075303963534 [0.974874,0.926108,0.985,0.936709,0.950495,0.925373,0.956743,0.968059,0.93199,0.944724]
kappa
0.9444444444444444
kb_relative_information_score
0.9444802515732746
mean_absolute_error
0.013791731034891215
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.95 [0.97,0.94,0.985,0.925,0.96,0.93,0.94,0.985,0.925,0.94]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9502471166951322 [0.979798,0.912621,0.985,0.948718,0.941176,0.920792,0.974093,0.951691,0.939086,0.949495]
predictive_accuracy
0.95
prior_entropy
3.3219280948872383
relative_absolute_error
0.07662072797161551
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.08771958173473939
root_relative_squared_error
0.2923986057824602
total_cost
0
unweighted_recall
0.95 [0.97,0.94,0.985,0.925,0.96,0.93,0.94,0.985,0.925,0.94]
area_under_roc_curve
0.9977777777777779 [0.997778,0.997222,1,0.998611,1,0.992222,0.9975,1,0.994444,1]
area_under_roc_curve
0.9985555555555556 [1,0.9975,1,0.995556,0.998333,0.995556,0.999722,0.999167,1,0.999722]
area_under_roc_curve
0.9980833333333333 [0.999722,0.998056,1,0.998333,1,0.990833,1,0.998056,0.998611,0.997222]
area_under_roc_curve
0.9974166666666667 [1,1,0.999722,0.989444,0.995833,0.994444,1,0.999444,0.999722,0.995556]
area_under_roc_curve
0.997361111111111 [0.999722,0.993611,1,0.990556,0.997778,0.993333,0.999722,1,0.999167,0.999722]
area_under_roc_curve
0.9967777777777778 [1,0.998056,1,1,0.996667,0.988333,0.996944,1,0.996389,0.991389]
area_under_roc_curve
0.9973888888888888 [0.993611,0.995278,0.999722,0.999444,1,0.997778,1,0.998333,0.995556,0.994167]
area_under_roc_curve
0.9985833333333334 [1,0.999722,1,0.998611,0.998056,0.999722,0.994444,1,0.995278,1]
area_under_roc_curve
0.9980000000000001 [0.996944,1,1,0.989167,1,0.993889,1,1,1,1]
area_under_roc_curve
0.9955833333333333 [1,0.998611,1,0.997778,0.999444,0.998611,0.966389,1,0.997222,0.997778]
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
0.94489729470474 [0.974359,0.923077,1,0.918919,0.952381,0.926829,0.947368,0.97561,0.878049,0.952381]
f_measure
0.955191590608792 [1,0.904762,1,0.9,0.947368,0.923077,0.974359,0.952381,0.97561,0.974359]
f_measure
0.9505016334454791 [0.974359,0.974359,1,0.918919,0.97561,0.878049,1,0.95,0.95,0.883721]
f_measure
0.9653027585106575 [0.974359,0.930233,0.952381,0.947368,0.95,0.974359,1,0.97561,0.974359,0.974359]
f_measure
0.9397936585035428 [0.97561,0.878049,0.947368,0.9,0.918919,0.9,0.952381,1,0.97561,0.95]
f_measure
0.9440984712935933 [0.97561,0.952381,1,1,0.95,0.926829,0.918919,0.952381,0.9,0.864865]
f_measure
0.9549104550503184 [0.974359,0.894737,0.974359,0.97561,0.97561,0.926829,1,0.930233,0.95,0.947368]
f_measure
0.958978317012917 [0.97561,0.930233,1,0.926829,0.97561,0.974359,0.95,1,0.857143,1]
f_measure
0.9503635196639046 [0.95,0.947368,0.97561,0.926829,0.909091,0.9,0.947368,1,0.947368,1]
f_measure
0.9351942708553749 [0.974359,0.926829,1,0.95,0.95,0.926829,0.871795,0.947368,0.904762,0.9]
kappa
0.9388888888888889
kappa
0.95
kappa
0.9444444444444444
kappa
0.961111111111111
kappa
0.9333333333333332
kappa
0.9388888888888889
kappa
0.95
kappa
0.9555555555555555
kappa
0.9444444444444444
kappa
0.9277777777777778
kb_relative_information_score
0.9390419286950329
kb_relative_information_score
0.9468296951355106
kb_relative_information_score
0.9442230866916251
kb_relative_information_score
0.9583420847989873
kb_relative_information_score
0.9257184619026709
kb_relative_information_score
0.9321642879637254
kb_relative_information_score
0.9462896587980826
kb_relative_information_score
0.9587907751822771
kb_relative_information_score
0.957009684961478
kb_relative_information_score
0.9363928516030379
mean_absolute_error
0.015551824809918593
mean_absolute_error
0.012602200977852713
mean_absolute_error
0.013866668371352801
mean_absolute_error
0.010538697095594945
mean_absolute_error
0.01875742438890405
mean_absolute_error
0.017063814524412097
mean_absolute_error
0.013448118643353397
mean_absolute_error
0.010165468467206219
mean_absolute_error
0.011607561289751498
mean_absolute_error
0.014315531780566033
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
precision
0.9479835953520164 [1,0.947368,1,1,0.909091,0.904762,1,0.952381,0.857143,0.909091]
precision
0.9572476646160857 [1,0.863636,1,0.9,1,0.947368,1,0.909091,0.952381,1]
precision
0.9535610766045549 [1,1,1,1,0.952381,0.857143,1,0.95,0.95,0.826087]
precision
0.9681037078863164 [1,0.869565,0.909091,1,0.95,1,1,0.952381,1,1]
precision
0.942099567099567 [0.952381,0.857143,1,0.9,1,0.9,0.909091,1,0.952381,0.95]
precision
0.946650114591291 [0.952381,0.909091,1,1,0.95,0.904762,1,0.909091,0.9,0.941176]
precision
0.9573533471359559 [1,0.944444,1,0.952381,0.952381,0.904762,1,0.869565,0.95,1]
precision
0.9629089026915113 [0.952381,0.869565,1,0.904762,0.952381,1,0.95,1,1,1]
precision
0.954047619047619 [0.95,1,0.952381,0.904762,0.833333,0.9,1,1,1,1]
precision
0.9367897015265437 [1,0.904762,1,0.95,0.95,0.904762,0.894737,1,0.863636,0.9]
predictive_accuracy
0.945
predictive_accuracy
0.955
predictive_accuracy
0.95
predictive_accuracy
0.965
predictive_accuracy
0.94
predictive_accuracy
0.945
predictive_accuracy
0.955
predictive_accuracy
0.96
predictive_accuracy
0.95
predictive_accuracy
0.935
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
relative_absolute_error
0.08639902672177005
relative_absolute_error
0.07001222765473737
relative_absolute_error
0.07703704650751565
relative_absolute_error
0.05854831719774976
relative_absolute_error
0.10420791327168928
relative_absolute_error
0.09479896958006732
relative_absolute_error
0.0747117702408523
relative_absolute_error
0.05647482481781238
relative_absolute_error
0.06448645160973061
relative_absolute_error
0.07953073211425582
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_squared_error
0.08775392611181179
root_mean_squared_error
0.0871637276587532
root_mean_squared_error
0.09085045989589895
root_mean_squared_error
0.07292418996867156
root_mean_squared_error
0.09786356564117855
root_mean_squared_error
0.09785930121034923
root_mean_squared_error
0.0841743717642475
root_mean_squared_error
0.07533500689647075
root_mean_squared_error
0.07905558822044736
root_mean_squared_error
0.0995642768046111
root_relative_squared_error
0.2925130870393728
root_relative_squared_error
0.2905457588625109
root_relative_squared_error
0.3028348663196634
root_relative_squared_error
0.24308063322890533
root_relative_squared_error
0.3262118854705954
root_relative_squared_error
0.3261976707011643
root_relative_squared_error
0.2805812392141585
root_relative_squared_error
0.2511166896549027
root_relative_squared_error
0.26351862740149135
root_relative_squared_error
0.33188092268203717
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
0.9450000000000001 [0.95,0.9,1,0.85,1,0.95,0.9,1,0.9,1]
unweighted_recall
0.9550000000000001 [1,0.95,1,0.9,0.9,0.9,0.95,1,1,0.95]
unweighted_recall
0.95 [0.95,0.95,1,0.85,1,0.9,1,0.95,0.95,0.95]
unweighted_recall
0.9649999999999999 [0.95,1,1,0.9,0.95,0.95,1,1,0.95,0.95]
unweighted_recall
0.9399999999999998 [1,0.9,0.9,0.9,0.85,0.9,1,1,1,0.95]
unweighted_recall
0.9450000000000001 [1,1,1,1,0.95,0.95,0.85,1,0.9,0.8]
unweighted_recall
0.9550000000000001 [0.95,0.85,0.95,1,1,0.95,1,1,0.95,0.9]
unweighted_recall
0.9600000000000002 [1,1,1,0.95,1,0.95,0.95,1,0.75,1]
unweighted_recall
0.95 [0.95,0.9,1,0.95,1,0.9,0.9,1,0.9,1]
unweighted_recall
0.9349999999999999 [0.95,0.95,1,0.95,0.95,0.95,0.85,0.9,0.95,0.9]
usercpu_time_millis
5796.784373999799
usercpu_time_millis
6567.250574999889
usercpu_time_millis
6446.10787900001
usercpu_time_millis
6980.074088000038
usercpu_time_millis
5800.259470999663
usercpu_time_millis
5885.632372000146
usercpu_time_millis
6347.7320820002205
usercpu_time_millis
7412.468594000529
usercpu_time_millis
6191.232377999768
usercpu_time_millis
7171.001391000573
usercpu_time_millis_testing
4.64410000040516
usercpu_time_millis_testing
3.0841999996482627
usercpu_time_millis_testing
4.158699999607052
usercpu_time_millis_testing
3.1260000005204347
usercpu_time_millis_testing
3.762000000278931
usercpu_time_millis_testing
3.7573999998130603
usercpu_time_millis_testing
4.638800000066112
usercpu_time_millis_testing
3.2973000006677466
usercpu_time_millis_testing
3.9608999995834893
usercpu_time_millis_testing
3.18589900052757
usercpu_time_millis_training
5792.140273999394
usercpu_time_millis_training
6564.166375000241
usercpu_time_millis_training
6441.949179000403
usercpu_time_millis_training
6976.948087999517
usercpu_time_millis_training
5796.497470999384
usercpu_time_millis_training
5881.8749720003325
usercpu_time_millis_training
6343.093282000154
usercpu_time_millis_training
7409.1712939998615
usercpu_time_millis_training
6187.271478000184
usercpu_time_millis_training
7167.815492000045
wall_clock_time_millis
5930.474042892456
wall_clock_time_millis
6949.768543243408
wall_clock_time_millis
6451.91764831543
wall_clock_time_millis
6993.796586990356
wall_clock_time_millis
5805.266380310059
wall_clock_time_millis
6166.12696647644
wall_clock_time_millis
6354.764223098755
wall_clock_time_millis
7540.453672409058
wall_clock_time_millis
6379.693984985352
wall_clock_time_millis
7194.236755371094
wall_clock_time_millis_testing
4.647254943847656
wall_clock_time_millis_testing
3.0875205993652344
wall_clock_time_millis_testing
4.162073135375977
wall_clock_time_millis_testing
3.129720687866211
wall_clock_time_millis_testing
3.7643909454345703
wall_clock_time_millis_testing
3.7610530853271484
wall_clock_time_millis_testing
4.644155502319336
wall_clock_time_millis_testing
3.2987594604492188
wall_clock_time_millis_testing
3.965616226196289
wall_clock_time_millis_testing
3.2024383544921875
wall_clock_time_millis_training
5925.826787948608
wall_clock_time_millis_training
6946.681022644043
wall_clock_time_millis_training
6447.755575180054
wall_clock_time_millis_training
6990.66686630249
wall_clock_time_millis_training
5801.501989364624
wall_clock_time_millis_training
6162.365913391113
wall_clock_time_millis_training
6350.120067596436
wall_clock_time_millis_training
7537.154912948608
wall_clock_time_millis_training
6375.728368759155
wall_clock_time_millis_training
7191.034317016602
weighted_recall
0.945 [0.95,0.9,1,0.85,1,0.95,0.9,1,0.9,1]
weighted_recall
0.955 [1,0.95,1,0.9,0.9,0.9,0.95,1,1,0.95]
weighted_recall
0.95 [0.95,0.95,1,0.85,1,0.9,1,0.95,0.95,0.95]
weighted_recall
0.965 [0.95,1,1,0.9,0.95,0.95,1,1,0.95,0.95]
weighted_recall
0.94 [1,0.9,0.9,0.9,0.85,0.9,1,1,1,0.95]
weighted_recall
0.945 [1,1,1,1,0.95,0.95,0.85,1,0.9,0.8]
weighted_recall
0.955 [0.95,0.85,0.95,1,1,0.95,1,1,0.95,0.9]
weighted_recall
0.96 [1,1,1,0.95,1,0.95,0.95,1,0.75,1]
weighted_recall
0.95 [0.95,0.9,1,0.95,1,0.9,0.9,1,0.9,1]
weighted_recall
0.935 [0.95,0.95,1,0.95,0.95,0.95,0.85,0.9,0.95,0.9]