Run
10228337

Run 10228337

Task 3954 (Supervised Classification) MagicTelescope 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.C376771ff9d5230(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_state51449
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.C376771ff9d5230(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C376771ff9d5230(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
0.8264 ± 0.0113
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7904 ± 0.0081
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5413 ± 0.0174
Cross-validation details (10-fold Crossvalidation)
KB relative information score
5628.3047 ± 21.0019
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3326 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
19020
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7909 ± 0.008
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.79 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9355
Cross-validation details (10-fold Crossvalidation)
Recall
0.79 ± 0.0084
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7294 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4002 ± 0.0057
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8381 ± 0.0119
Cross-validation details (10-fold Crossvalidation)