Run
10154821

Run 10154821

Task 31 (Supervised Classification) credit-g Uploaded 18-02-2019 by naruto u
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, estimator=sklearn.tree.tree.DecisionTreeClassifier)(11)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(11)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(11)_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(36)_axis0
sklearn.preprocessing.imputation.Imputer(36)_copytrue
sklearn.preprocessing.imputation.Imputer(36)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(36)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(36)_verbose0
sklearn.tree.tree.DecisionTreeClassifier(34)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(34)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(34)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(34)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(34)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(34)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(34)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(34)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(34)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(34)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(34)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(34)_random_state54208
sklearn.tree.tree.DecisionTreeClassifier(34)_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
0.6493 ± 0.0615
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6943 ± 0.0483
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2874 ± 0.1146
Cross-validation details (10-fold Crossvalidation)
KB relative information score
205.7247 ± 12.644
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.311 ± 0.0495
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
0.7018 ± 0.0502
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.689 ± 0.0495
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.689 ± 0.0495
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7402 ± 0.1179
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5577 ± 0.0442
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2169 ± 0.0965
Cross-validation details (10-fold Crossvalidation)