Run
10155028

Run 10155028

Task 54 (Supervised Classification) hepatitis Uploaded 25-03-2019 by Hugo Spee
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  • auto-jupyter-notebook openml-python Sklearn_0.20.1.
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sk learn.tree.tree.DecisionTreeClassifier)(1)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(32)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(32)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(32)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(32)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(32)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(32)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(32)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(32)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(32)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(32)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(32)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(32)_random_state11373
sklearn.tree.tree.DecisionTreeClassifier(32)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(1)_memorynull
sklearn.impute.SimpleImputer(5)_copytrue
sklearn.impute.SimpleImputer(5)_fill_valuenull
sklearn.impute.SimpleImputer(5)_missing_valuesNaN
sklearn.impute.SimpleImputer(5)_strategy"mean"
sklearn.impute.SimpleImputer(5)_verbose0

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
0.6381 ± 0.1456
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.77 ± 0.0863
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2861 ± 0.2639
Cross-validation details (10-fold Crossvalidation)
KB relative information score
31.2823 ± 3.451
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2258 ± 0.0693
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3299 ± 0.0138
Cross-validation details (10-fold Crossvalidation)
Number of instances
155
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7664 ± 0.1202
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7742 ± 0.0693
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7418
Cross-validation details (10-fold Crossvalidation)
Recall
0.7742 ± 0.0693
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6846 ± 0.1915
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4048 ± 0.0166
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4752 ± 0.071
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.174 ± 0.1542
Cross-validation details (10-fold Crossvalidation)