Run
9264762

Run 9264762

Task 9979 (Supervised Classification) cardiotocography Uploaded 09-10-2018 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=s klearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imp uter,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=skle arn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotenco der=sklearn.preprocessing._encoders.OneHotEncoder)),sgdclassifier=sklearn.l inear_model.stochastic_gradient.SGDClassifier)(1)Automatically created scikit-learn flow.
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_remainder"passthrough"
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_transformer_weightsnull
sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
sklearn.impute.MissingIndicator(1)_error_on_newfalse
sklearn.impute.MissingIndicator(1)_features"missing-only"
sklearn.impute.MissingIndicator(1)_missing_valuesNaN
sklearn.impute.MissingIndicator(1)_sparse"auto"
sklearn.preprocessing.imputation.Imputer(29)_axis0
sklearn.preprocessing.imputation.Imputer(29)_copytrue
sklearn.preprocessing.imputation.Imputer(29)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(29)_strategy"median"
sklearn.preprocessing.imputation.Imputer(29)_verbose0
sklearn.preprocessing.data.StandardScaler(14)_copytrue
sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
sklearn.preprocessing.data.StandardScaler(14)_with_stdtrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
sklearn.impute.SimpleImputer(1)_copytrue
sklearn.impute.SimpleImputer(1)_fill_value-1
sklearn.impute.SimpleImputer(1)_missing_valuesNaN
sklearn.impute.SimpleImputer(1)_strategy"constant"
sklearn.impute.SimpleImputer(1)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(3)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(3)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier)(1)_memorynull
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_alpha0.024436427634075702
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_averagetrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_class_weightnull
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_early_stoppingfalse
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_epsilon0.1
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_eta00.0
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_fit_intercepttrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_l1_ratio0.15
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_learning_rate"optimal"
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_loss"hinge"
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_max_iternull
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_n_iternull
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_n_iter_no_change5
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_n_jobsnull
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_penalty"l2"
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_power_t0.5
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_random_state39913
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_shuffletrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_tol5.292049940274078e-05
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_validation_fraction0.1
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_verbose0
sklearn.linear_model.stochastic_gradient.SGDClassifier(8)_warm_startfalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

15 Evaluation measures

Area under ROC curve
0.5
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
275.1598 ± 0.2484
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1455 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1679 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
2126
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2723 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.9174
Cross-validation details (10-fold Crossvalidation)
Recall
0.2723 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8666 ± 0.002
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2897 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3815 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.3167 ± 0.0015
Cross-validation details (10-fold Crossvalidation)