Run
10227971

Run 10227971

Task 3512 (Supervised Classification) synthetic_control Uploaded 08-05-2019 by joe zhou
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sk learn.tree.tree.DecisionTreeClassifier)(2)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.tree.tree.DecisionTreeClassifier(37)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(37)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(37)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(37)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(37)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(37)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(37)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(37)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(37)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(37)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(37)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(37)_random_state57268
sklearn.tree.tree.DecisionTreeClassifier(37)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]

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
0.946 ± 0.0267
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9098 ± 0.0463
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.892 ± 0.0535
Cross-validation details (10-fold Crossvalidation)
KB relative information score
540.5052 ± 2.9472
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.03 ± 0.0149
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2778
Cross-validation details (10-fold Crossvalidation)
Number of instances
600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9102 ± 0.0432
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.91 ± 0.0446
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.91 ± 0.0446
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.108 ± 0.0535
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3727
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1732 ± 0.043
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4648 ± 0.1153
Cross-validation details (10-fold Crossvalidation)