Run
10228322

Run 10228322

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 02-06-2019 by Felix Neutatz
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  • Baseline openml-python Sklearn_0.20.3.
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Flow

sklearn.pipeline.C376767b31c5274(n1=sklearn.impute.SimpleImputer,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.linear_model.logistic.LogisticRegression(23)_C0.001
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_state64046
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.C376767b31c5274(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C376767b31c5274(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
0.7521 ± 0.048
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6855 ± 0.0436
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2911 ± 0.0787
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-236.6723 ± 5.5862
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4124 ± 0.0201
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Number of instances
748
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7717 ± 0.0309
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6604 ± 0.0478
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7928
Cross-validation details (10-fold Crossvalidation)
Recall
0.6604 ± 0.0478
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.136 ± 0.0557
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4524 ± 0.0197
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0623 ± 0.0466
Cross-validation details (10-fold Crossvalidation)