OpenML
10228694

Run 10228694

Task 2079 (Supervised Classification) eucalyptus Uploaded 18-06-2019 by Felix Neutatz
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  • ComplexityDriven openml-python Sklearn_0.20.3.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.C58b96267ebecc(n3=sklearn.compose._column_transformer.C58b 96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0), n5=fastsklearnfeature.transformations.ImputationTransformation.C3773dd80f36 e0b,c=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(23)_C0.1
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_state8644
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.C58b96267ebecc(n3=sklearn.compose._column_transformer.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0),n5=fastsklearnfeature.transformations.ImputationTransformation.C3773dd80f36e0b,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58b96267ebecc(n3=sklearn.compose._column_transformer.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0),n5=fastsklearnfeature.transformations.ImputationTransformation.C3773dd80f36e0b,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.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0)(1)_n_jobsnull
sklearn.compose._column_transformer.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0)(1)_remainder"drop"
sklearn.compose._column_transformer.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C58b96267ebceb(n4=sklearn.preprocessing._function_transformer.C3773dd80f35aa0)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [14]}}]
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C3773dd80f35aa0(1)_validatefalse
fastsklearnfeature.transformations.ImputationTransformation.C3773dd80f36e0b(1)_strategy"mean"

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
0.7569 ± 0.0352
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4062 ± 0.0577
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2785 ± 0.0574
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.2489 ± 0.0202
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2746 ± 0.0052
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
0.4826 ± 0.082
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4171 ± 0.0479
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.2621 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
Recall
0.4171 ± 0.0479
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8768 ± 0.0169
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
0.3664 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9259 ± 0.0126
Cross-validation details (10-fold Crossvalidation)