Run
10315253

Run 10315253

Task 31 (Supervised Classification) credit-g Uploaded 09-08-2019 by Xiao Xiao
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, estimator=sklearn.tree.tree.DecisionTreeClassifier)(21)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(21)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(21)_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"}}]
sklearn.preprocessing.imputation.Imputer(47)_axis0
sklearn.preprocessing.imputation.Imputer(47)_copytrue
sklearn.preprocessing.imputation.Imputer(47)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(47)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(47)_verbose0
sklearn.tree.tree.DecisionTreeClassifier(48)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(48)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(48)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(48)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(48)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(48)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(48)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(48)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(48)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(48)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(48)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(48)_random_state46709
sklearn.tree.tree.DecisionTreeClassifier(48)_splitter"best"

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
0.6364 ± 0.0409
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6814 ± 0.0305
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2607 ± 0.0753
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.1701 ± 0.0792
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.325 ± 0.031
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6909 ± 0.0333
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.675 ± 0.031
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8813
Cross-validation details (10-fold Crossvalidation)
Recall
0.675 ± 0.031
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7735 ± 0.0738
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5701 ± 0.0274
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.244 ± 0.0599
Cross-validation details (10-fold Crossvalidation)