Run
10227968

Run 10227968

Task 3493 (Supervised Classification) monks-problems-2 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
0.9925 ± 0.0169
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9917 ± 0.0179
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9816 ± 0.0396
Cross-validation details (10-fold Crossvalidation)
KB relative information score
589.1033 ± 2.7053
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0083 ± 0.018
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4507 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
Number of instances
601
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9918 ± 0.0173
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9917 ± 0.018
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9279
Cross-validation details (10-fold Crossvalidation)
Recall
0.9917 ± 0.018
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0185 ± 0.0401
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4746 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0912 ± 0.0862
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.1922 ± 0.1819
Cross-validation details (10-fold Crossvalidation)