Run
10233146

Run 10233146

Task 31 (Supervised Classification) credit-g Uploaded 23-07-2019 by lucy lu
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sk learn.tree.tree.DecisionTreeClassifier)(6)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(6)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(6)_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.impute.SimpleImputer(14)_copytrue
sklearn.impute.SimpleImputer(14)_fill_valuenull
sklearn.impute.SimpleImputer(14)_missing_valuesNaN
sklearn.impute.SimpleImputer(14)_strategy"mean"
sklearn.impute.SimpleImputer(14)_verbose0
sklearn.tree.tree.DecisionTreeClassifier(46)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(46)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(46)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(46)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(46)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(46)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(46)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(46)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(46)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(46)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(46)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(46)_random_state17287
sklearn.tree.tree.DecisionTreeClassifier(46)_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
0.6386 ± 0.041
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6868 ± 0.0373
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.268 ± 0.0806
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.188 ± 0.1041
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.318 ± 0.0408
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
0.6933 ± 0.0343
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.682 ± 0.0408
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8813
Cross-validation details (10-fold Crossvalidation)
Recall
0.682 ± 0.0408
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7569 ± 0.097
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5639 ± 0.0355
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2306 ± 0.0776
Cross-validation details (10-fold Crossvalidation)