Run
10228779

Run 10228779

Task 2079 (Supervised Classification) eucalyptus Uploaded 21-06-2019 by Felix Neutatz
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  • openml-python RawFeatureBaseline Sklearn_0.20.3.
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Flow

sklearn.pipeline.C377643e0b517d1(n1=sklearn.impute.SimpleImputer,n2=sklearn .preprocessing._encoders.OneHotEncoder,n3=sklearn.preprocessing.data.Standa rdScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.impute.SimpleImputer(10)_copytrue
sklearn.impute.SimpleImputer(10)_fill_valuenull
sklearn.impute.SimpleImputer(10)_missing_valuesNaN
sklearn.impute.SimpleImputer(10)_strategy"mean"
sklearn.impute.SimpleImputer(10)_verbose0
sklearn.preprocessing.data.StandardScaler(25)_copytrue
sklearn.preprocessing.data.StandardScaler(25)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(25)_with_stdtrue
sklearn.preprocessing._encoders.OneHotEncoder(9)_categorical_features[0, 2, 3, 4, 9]
sklearn.preprocessing._encoders.OneHotEncoder(9)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(9)_handle_unknown"error"
sklearn.preprocessing._encoders.OneHotEncoder(9)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_sparsetrue
sklearn.linear_model.logistic.LogisticRegression(23)_C100
sklearn.linear_model.logistic.LogisticRegression(23)_class_weight"balanced"
sklearn.linear_model.logistic.LogisticRegression(23)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(23)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(23)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(23)_max_iter10000
sklearn.linear_model.logistic.LogisticRegression(23)_multi_class"auto"
sklearn.linear_model.logistic.LogisticRegression(23)_n_jobsnull
sklearn.linear_model.logistic.LogisticRegression(23)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(23)_random_state16223
sklearn.linear_model.logistic.LogisticRegression(23)_solver"lbfgs"
sklearn.linear_model.logistic.LogisticRegression(23)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(23)_verbose0
sklearn.linear_model.logistic.LogisticRegression(23)_warm_startfalse
sklearn.pipeline.C377643e0b517d1(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,n3=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C377643e0b517d1(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,n3=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n1", "step_name": "n1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n2", "step_name": "n2"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n3", "step_name": "n3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]

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.

17 Evaluation measures

Area under ROC curve
0.8982 ± 0.0204
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6441 ± 0.044
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5463 ± 0.0545
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.5787 ± 0.0438
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1617 ± 0.0132
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3132 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
736
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.652 ± 0.0512
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6413 ± 0.0427
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.2621 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
Recall
0.6413 ± 0.0427
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5163 ± 0.0426
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3957 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3224 ± 0.02
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8148 ± 0.0511
Cross-validation details (10-fold Crossvalidation)