10218725
1
Jan van Rijn
3485
Supervised Classification
9666
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4)
8144157
copy
true
9559
fill_value
-1
9559
missing_values
NaN
9559
strategy
"constant"
9559
verbose
0
9559
n_jobs
null
9606
remainder
"passthrough"
9606
sparse_threshold
0.3
9606
transformer_weights
null
9606
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [294, 295, 296, 297, 298]}}]
9606
memory
null
9607
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
9607
axis
0
9608
copy
true
9608
missing_values
"NaN"
9608
strategy
"mean"
9608
verbose
0
9608
copy
true
9609
with_mean
true
9609
with_std
true
9609
memory
null
9610
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
9610
categorical_features
null
9611
categories
null
9611
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
9611
handle_unknown
"ignore"
9611
n_values
null
9611
sparse
true
9611
threshold
0.0
9612
memory
null
9666
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
9666
criterion
"mse"
9667
init
null
9667
learning_rate
5.2182428883519156e-05
9667
loss
"deviance"
9667
max_depth
6
9667
max_features
0.6762760462190054
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.45212479265123307
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min_impurity_split
null
9667
min_samples_leaf
16
9667
min_samples_split
17
9667
min_weight_fraction_leaf
0.13986944426582493
9667
n_estimators
826
9667
n_iter_no_change
463
9667
presort
"auto"
9667
random_state
64984
9667
subsample
0.07148342340855629
9667
tol
6.020332684724282e-05
9667
validation_fraction
0.41486746387384055
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
312
scene
https://www.openml.org/data/download/1390080/phpuZu33P
-1
21358366
description
https://api.openml.org/data/download/21358366/description.xml
-1
21358367
predictions
https://api.openml.org/data/download/21358367/predictions.arff
area_under_roc_curve
0.4998925622551829 [0.499893,0.499893]
average_cost
0
kappa
0
kb_relative_information_score
-70.23747342641047
mean_absolute_error
0.2966573743469775
mean_prior_absolute_error
0.29416743712946186
number_of_instances
2407 [1976,431]
predictive_accuracy
0.8209389281262983
prior_entropy
0.6786037019780878
recall
0.8209389281262983 [1,0]
relative_absolute_error
1.0084643536409497
root_mean_prior_squared_error
0.3834035412052162
root_mean_squared_error
0.38342756227698804
root_relative_squared_error
1.0000626521906824
total_cost
0
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
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
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kb_relative_information_score
-8.314131844460292
kb_relative_information_score
-8.314131844460292
kb_relative_information_score
-8.314131844460292
kb_relative_information_score
-8.314131844460292
kb_relative_information_score
-8.314131844460292
kb_relative_information_score
-8.314131844460292
kb_relative_information_score
-8.206852723886607
kb_relative_information_score
-4.048609878587307
kb_relative_information_score
-4.048609878587307
kb_relative_information_score
-4.048609878587307
mean_absolute_error
0.29670535532188813
mean_absolute_error
0.29670535532188813
mean_absolute_error
0.29670535532188813
mean_absolute_error
0.29670535532188813
mean_absolute_error
0.29670535532188813
mean_absolute_error
0.29670535532188813
mean_absolute_error
0.2993285120274121
mean_absolute_error
0.2956669234154621
mean_absolute_error
0.2956669234154621
mean_absolute_error
0.2956669234154621
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.29641954703058604
mean_prior_absolute_error
0.2942351598173521
mean_prior_absolute_error
0.2942351598173521
mean_prior_absolute_error
0.2942351598173521
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [197,44]
number_of_instances
240 [197,43]
number_of_instances
240 [197,43]
number_of_instances
240 [197,43]
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8174273858921162
predictive_accuracy
0.8208333333333333
predictive_accuracy
0.8208333333333333
predictive_accuracy
0.8208333333333333
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8174273858921162 [1,0]
recall
0.8208333333333333 [1,0]
recall
0.8208333333333333 [1,0]
recall
0.8208333333333333 [1,0]
relative_absolute_error
1.0100320230427564
relative_absolute_error
1.0100320230427564
relative_absolute_error
1.0100320230427564
relative_absolute_error
1.0100320230427564
relative_absolute_error
1.0100320230427564
relative_absolute_error
1.0100320230427564
relative_absolute_error
1.009813674657987
relative_absolute_error
1.0048660520347017
relative_absolute_error
1.0048660520347017
relative_absolute_error
1.0048660520347017
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3863293741224291
root_mean_prior_squared_error
0.38349184880071946
root_mean_prior_squared_error
0.38349184880071946
root_mean_prior_squared_error
0.38349184880071946
root_mean_squared_error
0.3829079335256263
root_mean_squared_error
0.3829079335256263
root_mean_squared_error
0.3829079335256263
root_mean_squared_error
0.3829079335256263
root_mean_squared_error
0.3829079335256263
root_mean_squared_error
0.3829079335256263
root_mean_squared_error
0.38631805842128253
root_mean_squared_error
0.3834992760404476
root_mean_squared_error
0.3834992760404476
root_mean_squared_error
0.3834992760404476
root_relative_squared_error
1.0000998749429832
root_relative_squared_error
1.0000998749429832
root_relative_squared_error
1.0000998749429832
root_relative_squared_error
1.0000998749429832
root_relative_squared_error
1.0000998749429832
root_relative_squared_error
1.0000998749429832
root_relative_squared_error
0.9999707097054882
root_relative_squared_error
1.0000193673992064
root_relative_squared_error
1.0000193673992064
root_relative_squared_error
1.0000193673992064
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
usercpu_time_millis
821.0317189987109
usercpu_time_millis
770.5074350014911
usercpu_time_millis
781.4101670010132
usercpu_time_millis
773.3143599980394
usercpu_time_millis
789.8506839956099
usercpu_time_millis
796.660879997944
usercpu_time_millis
769.9849529999483
usercpu_time_millis
774.0853929972218
usercpu_time_millis
797.5207380004576
usercpu_time_millis
770.7420890001231
usercpu_time_millis_testing
4.106366999621969
usercpu_time_millis_testing
4.026182999950834
usercpu_time_millis_testing
4.026096001325641
usercpu_time_millis_testing
4.088559999217978
usercpu_time_millis_testing
4.123160997551167
usercpu_time_millis_testing
4.065913999511395
usercpu_time_millis_testing
4.010696000477765
usercpu_time_millis_testing
4.06481399841141
usercpu_time_millis_testing
4.067677000421099
usercpu_time_millis_testing
3.9680369991401676
usercpu_time_millis_training
816.9253519990889
usercpu_time_millis_training
766.4812520015403
usercpu_time_millis_training
777.3840709996875
usercpu_time_millis_training
769.2257999988215
usercpu_time_millis_training
785.7275229980587
usercpu_time_millis_training
792.5949659984326
usercpu_time_millis_training
765.9742569994705
usercpu_time_millis_training
770.0205789988104
usercpu_time_millis_training
793.4530610000365
usercpu_time_millis_training
766.7740520009829