Run
10228790

Run 10228790

Task 3656 (Supervised Classification) diabetes_numeric Uploaded 21-06-2019 by Felix Neutatz
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  • ComplexityDriven openml-python Sklearn_0.20.3.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.C58bd4af663509(n3=sklearn.compose._column_transformer.C58b d4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a), n5=fastsklearnfeature.transformations.OneDivisionTransformation.C58bd4af663 4de,c=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(23)_C10
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_state26906
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.C58bd4af663509(n3=sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a),n5=fastsklearnfeature.transformations.OneDivisionTransformation.C58bd4af6634de,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58bd4af663509(n3=sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a),n5=fastsklearnfeature.transformations.OneDivisionTransformation.C58bd4af6634de,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n3", "step_name": "n3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n5", "step_name": "n5"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]
sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a)(1)_n_jobsnull
sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a)(1)_remainder"drop"
sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C58bd4af663476(n4=sklearn.preprocessing._function_transformer.C37764ed9fe0a2a)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C37764ed9fe0a2a(1)_validatefalse

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
0.5747 ± 0.403
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6849 ± 0.1596
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3337 ± 0.4008
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0839 ± 0.1365
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4406 ± 0.0441
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4791 ± 0.0218
Cross-validation details (10-fold Crossvalidation)
Number of instances
43
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6927 ± 0.1652
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6977 ± 0.1657
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9682 ± 0.0639
Cross-validation details (10-fold Crossvalidation)
Recall
0.6977 ± 0.1657
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9198 ± 0.1155
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4889 ± 0.0226
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4587 ± 0.0335
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9381 ± 0.0886
Cross-validation details (10-fold Crossvalidation)