Run
10194967

Run 10194967

Task 3022 (Supervised Classification) vowel Uploaded 17-04-2019 by yang hua
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, estimator=sklearn.tree.tree.DecisionTreeClassifier)(13)Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(38)_axis0
sklearn.preprocessing.imputation.Imputer(38)_copytrue
sklearn.preprocessing.imputation.Imputer(38)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(38)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(38)_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_state48439
sklearn.tree.tree.DecisionTreeClassifier(37)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(13)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(13)_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
0.9 ± 0.0282
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8175 ± 0.0516
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8 ± 0.0564
Cross-validation details (10-fold Crossvalidation)
KB relative information score
802.8455 ± 5.279
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0331 ± 0.0093
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1653
Cross-validation details (10-fold Crossvalidation)
Number of instances
990
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8188 ± 0.0452
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8182 ± 0.0513
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.4594
Cross-validation details (10-fold Crossvalidation)
Recall
0.8182 ± 0.0513
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2 ± 0.0564
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2875
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1818 ± 0.026
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6325 ± 0.0904
Cross-validation details (10-fold Crossvalidation)