Run
10228773

Run 10228773

Task 59 (Supervised Classification) iris Uploaded 21-06-2019 by Felix Neutatz
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  • openml-python RawFeatureBaseline Sklearn_0.20.3.
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Flow

sklearn.pipeline.C3776429d2b50e6(n1=sklearn.impute.SimpleImputer,n2=sklearn .preprocessing.data.MinMaxScaler,c=sklearn.linear_model.logistic.LogisticRe gression)(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.preprocessing.data.MinMaxScaler(6)_copytrue
sklearn.preprocessing.data.MinMaxScaler(6)_feature_range[0, 1]
sklearn.linear_model.logistic.LogisticRegression(23)_C100
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_state12372
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.C3776429d2b50e6(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing.data.MinMaxScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C3776429d2b50e6(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing.data.MinMaxScaler,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": "n2", "step_name": "n2"}}, {"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
0.9983 ± 0.0042
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9733 ± 0.0348
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.96 ± 0.0516
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9328 ± 0.0468
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0385 ± 0.0232
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9738 ± 0.0287
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9733 ± 0.0344
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9733 ± 0.0344
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0865 ± 0.0522
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1164 ± 0.0588
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2469 ± 0.1248
Cross-validation details (10-fold Crossvalidation)