Run
10228332

Run 10228332

Task 38 (Supervised Classification) ecoli Uploaded 02-06-2019 by Felix Neutatz
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  • openml-python RawFeatureBaseline Sklearn_0.20.3.
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Flow

sklearn.pipeline.C58a57c601a9c1(n1=sklearn.impute.SimpleImputer,c=sklearn.l inear_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.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_state41785
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.C58a57c601a9c1(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58a57c601a9c1(n1=sklearn.impute.SimpleImputer,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": "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
0.964 ± 0.0242
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8512 ± 0.0665
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7817 ± 0.1006
Cross-validation details (10-fold Crossvalidation)
KB relative information score
214.1644 ± 2.6875
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0828 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1828 ± 0.002
Cross-validation details (10-fold Crossvalidation)
Number of instances
336
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8702 ± 0.0604
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8393 ± 0.0758
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.2353
Cross-validation details (10-fold Crossvalidation)
Recall
0.8393 ± 0.0758
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4532 ± 0.0679
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3016 ± 0.0033
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1859 ± 0.0245
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6165 ± 0.0799
Cross-validation details (10-fold Crossvalidation)