10448797
8323
Heinrich Peters
9977
Supervised Classification
17651
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
8264351
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"most_frequent"
12737
verbose
0
12737
copy
true
13294
with_mean
true
13294
with_std
true
13294
categorical_features
null
16348
categories
null
16348
drop
null
16348
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
16348
handle_unknown
"ignore"
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n_values
null
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sparse
true
16348
n_jobs
null
16375
remainder
"drop"
16375
sparse_threshold
0.3
16375
transformer_weights
null
16375
transformers
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16375
verbose
false
16375
memory
null
16376
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
16376
verbose
false
16376
memory
null
16377
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
16377
verbose
false
16377
bootstrap
false
17650
class_weight
null
17650
criterion
"gini"
17650
max_depth
null
17650
max_features
0.21975649694764154
17650
max_leaf_nodes
null
17650
min_impurity_decrease
0
17650
min_impurity_split
null
17650
min_samples_leaf
2
17650
min_samples_split
4
17650
min_weight_fraction_leaf
0.0
17650
n_estimators
300
17650
n_jobs
1
17650
oob_score
false
17650
random_state
1
17650
verbose
0
17650
warm_start
false
17650
memory
null
17651
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}]
17651
verbose
false
17651
openml-python
Sklearn_0.21.2.
1486
nomao
https://www.openml.org/data/download/1592278/phpDYCOet
-1
21822025
description
https://api.openml.org/data/download/21822025/description.xml
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21822026
predictions
https://api.openml.org/data/download/21822026/predictions.arff
area_under_roc_curve
0.9947393301740396 [0.99474,0.994739]
average_cost
0
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0.9265080656554294
kb_relative_information_score
0.8771788893091934
mean_absolute_error
0.052884544514336614
mean_prior_absolute_error
0.4080904194746198
weighted_recall
0.9700565791382562 [0.944941,0.980098]
number_of_instances
34465 [9844,24621]
precision
0.9700142224609898 [0.949959,0.978033]
predictive_accuracy
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prior_entropy
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root_relative_squared_error
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total_cost
0
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0.9625196854695073 [0.944941,0.980098]
area_under_roc_curve
0.9940970142380585 [0.994098,0.994097]
area_under_roc_curve
0.9948585284781521 [0.99486,0.994858]
area_under_roc_curve
0.993829102967259 [0.993828,0.993829]
area_under_roc_curve
0.9952971902943786 [0.995298,0.995297]
area_under_roc_curve
0.995286910742203 [0.995287,0.995287]
area_under_roc_curve
0.9952690887858812 [0.99527,0.995269]
area_under_roc_curve
0.9943029816652765 [0.994302,0.994303]
area_under_roc_curve
0.9960589405327448 [0.996058,0.996059]
area_under_roc_curve
0.9944877285809041 [0.99449,0.994487]
area_under_roc_curve
0.9941633736014444 [0.994165,0.994163]
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0
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0
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0
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0
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0
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0
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0
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0
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0
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0
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0.9712749873673682 [0.94967,0.979907]
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f_measure
0.9727299100667247 [0.952284,0.98091]
f_measure
0.9712485506773203 [0.949567,0.979923]
f_measure
0.966856900897385 [0.941718,0.976904]
f_measure
0.9666431994123715 [0.941654,0.976631]
f_measure
0.9744078630567096 [0.954964,0.982179]
f_measure
0.9701057094746782 [0.947636,0.979086]
f_measure
0.970528740822953 [0.94775,0.979633]
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kb_relative_information_score
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kb_relative_information_score
0.8685190040736963
kb_relative_information_score
0.8824291458785699
kb_relative_information_score
0.8801761657155699
kb_relative_information_score
0.8729853808568627
kb_relative_information_score
0.87610607929041
kb_relative_information_score
0.8892716680166692
kb_relative_information_score
0.8758436179721824
kb_relative_information_score
0.876840512711829
mean_absolute_error
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mean_absolute_error
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number_of_instances
3447 [984,2463]
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3447 [985,2462]
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precision
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precision
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precision
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precision
0.9666601888715963 [0.940223,0.977227]
precision
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unweighted_recall
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unweighted_recall
0.9587452860718697 [0.930894,0.986596]
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weighted_recall
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weighted_recall
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weighted_recall
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weighted_recall
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weighted_recall
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