Run
10227978

Run 10227978

Task 3889 (Supervised Classification) sylva_agnostic 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
0.9581 ± 0.0125
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9905 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.918 ± 0.0218
Cross-validation details (10-fold Crossvalidation)
KB relative information score
12709.1709 ± 44.2303
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0094 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1156 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
14395
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9905 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9906 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3338
Cross-validation details (10-fold Crossvalidation)
Recall
0.9906 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0817 ± 0.0217
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2403 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0972 ± 0.0123
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4044 ± 0.0511
Cross-validation details (10-fold Crossvalidation)