10227101
1
Jan van Rijn
49
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)
8152533
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": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8]}}]
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
"friedman_mse"
9667
init
null
9667
learning_rate
1.9687418798919585e-05
9667
loss
"deviance"
9667
max_depth
24
9667
max_features
0.7805735684922522
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.36004711135664325
9667
min_impurity_split
null
9667
min_samples_leaf
10
9667
min_samples_split
4
9667
min_weight_fraction_leaf
0.42569010499862664
9667
n_estimators
1299
9667
n_iter_no_change
1160
9667
presort
"auto"
9667
random_state
40960
9667
subsample
0.7620199927305592
9667
tol
0.0001929105199465155
9667
validation_fraction
0.45722992205736634
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
50
tic-tac-toe
https://www.openml.org/data/download/50/dataset_50_tic-tac-toe.arff
-1
21375118
description
https://api.openml.org/data/download/21375118/description.xml
-1
21375119
predictions
https://api.openml.org/data/download/21375119/predictions.arff
area_under_roc_curve
0.6239294237653491 [0.623929,0.623929]
average_cost
0
kappa
0
kb_relative_information_score
3.350950321608299
mean_absolute_error
0.45144498075647965
mean_prior_absolute_error
0.45300756784968915
number_of_instances
958 [332,626]
predictive_accuracy
0.6534446764091858
prior_entropy
0.9312461581068427
recall
0.6534446764091858 [0,1]
relative_absolute_error
0.996550637993474
root_mean_prior_squared_error
0.47587270721768155
root_mean_squared_error
0.4752490336652028
root_relative_squared_error
0.9986894109642783
total_cost
0
area_under_roc_curve
0.6618566618566618 [0.661857,0.661857]
area_under_roc_curve
0.6972101972101972 [0.69721,0.69721]
area_under_roc_curve
0.7895622895622895 [0.789562,0.789562]
area_under_roc_curve
0.6758056758056759 [0.675806,0.675806]
area_under_roc_curve
0.7448292448292447 [0.744829,0.744829]
area_under_roc_curve
0.8128908128908129 [0.812891,0.812891]
area_under_roc_curve
0.683111954459203 [0.683112,0.683112]
area_under_roc_curve
0.7084914611005693 [0.708491,0.708491]
area_under_roc_curve
0.6898826979472141 [0.689883,0.689883]
area_under_roc_curve
0.7766373411534702 [0.776637,0.776637]
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
0.4387275497016338
kb_relative_information_score
0.37914692168659636
kb_relative_information_score
0.484712767621463
kb_relative_information_score
0.40189477238071203
kb_relative_information_score
0.44913500315157273
kb_relative_information_score
0.4608995528131171
kb_relative_information_score
0.5343779616173057
kb_relative_information_score
0.5872054704058267
kb_relative_information_score
-0.27805229389336183
kb_relative_information_score
-0.10709738387656456
mean_absolute_error
0.45021224431397006
mean_absolute_error
0.45047581270833675
mean_absolute_error
0.45000939257794753
mean_absolute_error
0.4503752938790633
mean_absolute_error
0.4501666133392654
mean_absolute_error
0.45011490502036305
mean_absolute_error
0.4529767364734205
mean_absolute_error
0.4527426688545062
mean_absolute_error
0.4539152056714797
mean_absolute_error
0.4535081576620813
mean_prior_absolute_error
0.45214843750000067
mean_prior_absolute_error
0.45214843750000067
mean_prior_absolute_error
0.45214843750000067
mean_prior_absolute_error
0.45214843750000067
mean_prior_absolute_error
0.45214843750000067
mean_prior_absolute_error
0.45214843750000067
mean_prior_absolute_error
0.4553385416666673
mean_prior_absolute_error
0.4553385416666673
mean_prior_absolute_error
0.45325657894736904
mean_prior_absolute_error
0.45325657894736904
number_of_instances
96 [33,63]
number_of_instances
96 [33,63]
number_of_instances
96 [33,63]
number_of_instances
96 [33,63]
number_of_instances
96 [33,63]
number_of_instances
96 [33,63]
number_of_instances
96 [34,62]
number_of_instances
96 [34,62]
number_of_instances
95 [33,62]
number_of_instances
95 [33,62]
predictive_accuracy
0.65625
predictive_accuracy
0.65625
predictive_accuracy
0.65625
predictive_accuracy
0.65625
predictive_accuracy
0.65625
predictive_accuracy
0.65625
predictive_accuracy
0.6458333333333333
predictive_accuracy
0.6458333333333333
predictive_accuracy
0.6526315789473683
predictive_accuracy
0.6526315789473683
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
prior_entropy
0.9312461581068427
recall
0.65625 [0,1]
recall
0.65625 [0,1]
recall
0.65625 [0,1]
recall
0.65625 [0,1]
recall
0.65625 [0,1]
recall
0.65625 [0,1]
recall
0.6458333333333334 [0,1]
recall
0.6458333333333334 [0,1]
recall
0.6526315789473685 [0,1]
recall
0.6526315789473685 [0,1]
relative_absolute_error
0.9957177930399669
relative_absolute_error
0.9963007175234043
relative_absolute_error
0.9952691533473383
relative_absolute_error
0.9960784037411665
relative_absolute_error
0.9956168726985034
relative_absolute_error
0.9955025113193328
relative_absolute_error
0.9948130786719659
relative_absolute_error
0.9942990268237354
relative_absolute_error
1.0014530990937631
relative_absolute_error
1.0005550470228066
root_mean_prior_squared_error
0.47496916018305874
root_mean_prior_squared_error
0.47496916018305874
root_mean_prior_squared_error
0.47496916018305874
root_mean_prior_squared_error
0.47496916018305874
root_mean_prior_squared_error
0.47496916018305874
root_mean_prior_squared_error
0.47496916018305874
root_mean_prior_squared_error
0.4783155938203006
root_mean_prior_squared_error
0.4783155938203006
root_mean_prior_squared_error
0.4761342715793188
root_mean_prior_squared_error
0.4761342715793188
root_mean_squared_error
0.4743857847592499
root_mean_squared_error
0.47444093840685947
root_mean_squared_error
0.4741205699579967
root_mean_squared_error
0.47448008090980637
root_mean_squared_error
0.4742869590232581
root_mean_squared_error
0.47420663924061107
root_mean_squared_error
0.47786713652942603
root_mean_squared_error
0.4776955025389946
root_mean_squared_error
0.4756662963541025
root_mean_squared_error
0.4753263349516632
root_relative_squared_error
0.9987717614685045
root_relative_squared_error
0.9988878819500708
root_relative_squared_error
0.9982133782649488
root_relative_squared_error
0.9989702925700189
root_relative_squared_error
0.998563693778481
root_relative_squared_error
0.9983945885199078
root_relative_squared_error
0.9990624238543161
root_relative_squared_error
0.9987035938419793
root_relative_squared_error
0.9990171360199213
root_relative_squared_error
0.998303132801225
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
883.8130489966716
usercpu_time_millis
811.157928998
usercpu_time_millis
813.3047359951888
usercpu_time_millis
815.016658991226
usercpu_time_millis
808.5610300040571
usercpu_time_millis
807.438377996732
usercpu_time_millis
809.8308939952403
usercpu_time_millis
807.2975559916813
usercpu_time_millis
832.2525520052295
usercpu_time_millis
808.6776409909362
usercpu_time_millis_testing
2.615589000924956
usercpu_time_millis_testing
2.4823540006764233
usercpu_time_millis_testing
2.6023469981737435
usercpu_time_millis_testing
2.6382679934613407
usercpu_time_millis_testing
2.6034039983642288
usercpu_time_millis_testing
2.572277997387573
usercpu_time_millis_testing
2.517184999305755
usercpu_time_millis_testing
2.813223996781744
usercpu_time_millis_testing
2.6532740012044087
usercpu_time_millis_testing
3.504643995256629
usercpu_time_millis_training
881.1974599957466
usercpu_time_millis_training
808.6755749973236
usercpu_time_millis_training
810.7023889970151
usercpu_time_millis_training
812.3783909977647
usercpu_time_millis_training
805.9576260056929
usercpu_time_millis_training
804.8660999993444
usercpu_time_millis_training
807.3137089959346
usercpu_time_millis_training
804.4843319948995
usercpu_time_millis_training
829.5992780040251
usercpu_time_millis_training
805.1729969956796