10225766
1
Jan van Rijn
9983
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)
8151198
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]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]
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
"most_frequent"
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
0.008450267356125375
9667
loss
"deviance"
9667
max_depth
3
9667
max_features
0.4524419153287036
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.5720450011377862
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min_impurity_split
null
9667
min_samples_leaf
18
9667
min_samples_split
14
9667
min_weight_fraction_leaf
0.049346694074198505
9667
n_estimators
459
9667
n_iter_no_change
1672
9667
presort
"auto"
9667
random_state
18722
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subsample
0.7827750462691007
9667
tol
0.07246260029162718
9667
validation_fraction
0.7975657164605423
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
1471
eeg-eye-state
https://www.openml.org/data/download/1587924/phplE7q6h
-1
21372448
description
https://api.openml.org/data/download/21372448/description.xml
-1
21372449
predictions
https://api.openml.org/data/download/21372449/predictions.arff
area_under_roc_curve
0.8144845877933978 [0.814485,0.814485]
average_cost
0
f_measure
0.740073063375651 [0.780735,0.690133]
kappa
0.4734377643521868
kb_relative_information_score
3520.1730515120225
mean_absolute_error
0.3958250172602414
mean_prior_absolute_error
0.4947574918117115
number_of_instances
14980 [8257,6723]
precision
0.7442392773223234 [0.737403,0.752635]
predictive_accuracy
0.7431909212283044
prior_entropy
0.9924243999391255
recall
0.7431909212283044 [0.829478,0.637216]
relative_absolute_error
0.8000384507787897
root_mean_prior_squared_error
0.4973714869043071
root_mean_squared_error
0.4260896190391573
root_relative_squared_error
0.8566828422175632
total_cost
0
area_under_roc_curve
0.827762884814943 [0.827763,0.827763]
area_under_roc_curve
0.8180884641992391 [0.818088,0.818088]
area_under_roc_curve
0.8138520768476882 [0.813852,0.813852]
area_under_roc_curve
0.8060134541104577 [0.806013,0.806013]
area_under_roc_curve
0.8239489651792921 [0.823949,0.823949]
area_under_roc_curve
0.8238426726622853 [0.823843,0.823843]
area_under_roc_curve
0.8247326472962067 [0.824733,0.824733]
area_under_roc_curve
0.8044108244405421 [0.804411,0.804411]
area_under_roc_curve
0.8082606150659641 [0.808261,0.808261]
area_under_roc_curve
0.7980872619208429 [0.798087,0.798087]
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
0.7483521881595019 [0.788876,0.698541]
f_measure
0.7349139246562348 [0.777273,0.682848]
f_measure
0.7485367103841422 [0.785755,0.702789]
f_measure
0.7313937926945286 [0.774816,0.678021]
f_measure
0.7451455786230149 [0.790151,0.689826]
f_measure
0.748692294588434 [0.787913,0.700483]
f_measure
0.7365676486319864 [0.782267,0.680395]
f_measure
0.7339652953085413 [0.772072,0.687253]
f_measure
0.7455853455791148 [0.786606,0.6953]
f_measure
0.7270274534181966 [0.760729,0.685714]
kappa
0.4902543349640141
kappa
0.4629999487888564
kappa
0.4903916135704892
kappa
0.4559205891770734
kappa
0.484327408721132
kappa
0.4908281525827002
kappa
0.4668276269488609
kappa
0.4610205185847768
kappa
0.4848778060883864
kappa
0.4470961224197377
kb_relative_information_score
380.03346683808434
kb_relative_information_score
355.18242564213074
kb_relative_information_score
351.35892958815947
kb_relative_information_score
339.2685524952065
kb_relative_information_score
358.0739100399338
kb_relative_information_score
354.45140664998115
kb_relative_information_score
353.69115672293697
kb_relative_information_score
340.495848280703
kb_relative_information_score
355.2927837046448
kb_relative_information_score
332.3245715502229
mean_absolute_error
0.3876220000200914
mean_absolute_error
0.3950383817603672
mean_absolute_error
0.3963084798192364
mean_absolute_error
0.3996572514864823
mean_absolute_error
0.39408856255390423
mean_absolute_error
0.3955993415212358
mean_absolute_error
0.3950792506307291
mean_absolute_error
0.39910210085530495
mean_absolute_error
0.39466711428426127
mean_absolute_error
0.40108768967081715
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.494736986564547
mean_prior_absolute_error
0.49480533738838384
mean_prior_absolute_error
0.49480533738838384
mean_prior_absolute_error
0.49480533738838384
number_of_instances
1498 [826,672]
number_of_instances
1498 [826,672]
number_of_instances
1498 [826,672]
number_of_instances
1498 [826,672]
number_of_instances
1498 [826,672]
number_of_instances
1498 [826,672]
number_of_instances
1498 [826,672]
number_of_instances
1498 [825,673]
number_of_instances
1498 [825,673]
number_of_instances
1498 [825,673]
precision
0.7534593325618368 [0.742521,0.766904]
precision
0.7394635737987341 [0.732334,0.748227]
precision
0.7515295877449023 [0.747541,0.756432]
precision
0.7361785915654925 [0.728922,0.745098]
precision
0.753440896253962 [0.734651,0.776536]
precision
0.7529316917414387 [0.744612,0.763158]
precision
0.7438442629254822 [0.729079,0.761993]
precision
0.7362491011933878 [0.736784,0.735593]
precision
0.7508761551279663 [0.739594,0.764706]
precision
0.7274615063253376 [0.738584,0.713826]
predictive_accuracy
0.7516688918558078
predictive_accuracy
0.7383177570093459
predictive_accuracy
0.7510013351134845
predictive_accuracy
0.7349799732977302
predictive_accuracy
0.7496662216288386
predictive_accuracy
0.7516688918558078
predictive_accuracy
0.7409879839786382
predictive_accuracy
0.7363150867823766
predictive_accuracy
0.7489986648865155
predictive_accuracy
0.7283044058744993
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
prior_entropy
0.9924243999391255
recall
0.7516688918558078 [0.841404,0.641369]
recall
0.7383177570093458 [0.828087,0.627976]
recall
0.7510013351134847 [0.828087,0.65625]
recall
0.7349799732977303 [0.826877,0.622024]
recall
0.7496662216288384 [0.854722,0.620536]
recall
0.7516688918558078 [0.836562,0.647321]
recall
0.7409879839786382 [0.843826,0.614583]
recall
0.7363150867823764 [0.810909,0.644874]
recall
0.7489986648865153 [0.84,0.637444]
recall
0.7283044058744993 [0.784242,0.659733]
relative_absolute_error
0.7834910478631041
relative_absolute_error
0.7984816023227073
relative_absolute_error
0.8010488210537925
relative_absolute_error
0.8078176128728555
relative_absolute_error
0.7965617555510751
relative_absolute_error
0.799615456827429
relative_absolute_error
0.7985642095897437
relative_absolute_error
0.8065840658910288
relative_absolute_error
0.7976209722541415
relative_absolute_error
0.8105969345193106
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4973508728636661
root_mean_prior_squared_error
0.4974195830102464
root_mean_prior_squared_error
0.4974195830102464
root_mean_prior_squared_error
0.4974195830102464
root_mean_squared_error
0.41911568571407115
root_mean_squared_error
0.4252080311258201
root_mean_squared_error
0.4262507372142241
root_mean_squared_error
0.42916771971239615
root_mean_squared_error
0.4240679109520968
root_mean_squared_error
0.42380372881640493
root_mean_squared_error
0.42446381705893343
root_mean_squared_error
0.4292992347911796
root_mean_squared_error
0.4271825020853219
root_mean_squared_error
0.43219640840096657
root_relative_squared_error
0.8426961901179959
root_relative_squared_error
0.8549457823961198
root_relative_squared_error
0.8570423024693636
root_relative_squared_error
0.8629073419361218
root_relative_squared_error
0.8526533964048001
root_relative_squared_error
0.8521222178141791
root_relative_squared_error
0.8534494261866663
root_relative_squared_error
0.8630525404592614
root_relative_squared_error
0.8587971134954739
root_relative_squared_error
0.8688769464712927
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
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total_cost
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total_cost
0
usercpu_time_millis
1453.043327004707
usercpu_time_millis
1353.9982509973925
usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
13.6510480006109
usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
1355.6511829956435
usercpu_time_millis_training
1366.2829609966138