Run
10229157

Run 10229157

Task 31 (Supervised Classification) credit-g Uploaded 11-07-2019 by Prabhant Singh
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sk learn.tree.tree.DecisionTreeClassifier)(5)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(44)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(44)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(44)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(44)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(44)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(44)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(44)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(44)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(44)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(44)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(44)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(44)_random_state3655
sklearn.tree.tree.DecisionTreeClassifier(44)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(5)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(5)_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(13)_copytrue
sklearn.impute.SimpleImputer(13)_fill_valuenull
sklearn.impute.SimpleImputer(13)_missing_valuesNaN
sklearn.impute.SimpleImputer(13)_strategy"mean"
sklearn.impute.SimpleImputer(13)_verbose0

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
0.6479 ± 0.0567
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6953 ± 0.0429
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2867 ± 0.1035
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.2109 ± 0.1106
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.309 ± 0.0433
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
0.7011 ± 0.0457
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.691 ± 0.0433
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8813
Cross-validation details (10-fold Crossvalidation)
Recall
0.691 ± 0.0433
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7354 ± 0.1031
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5559 ± 0.0381
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.213 ± 0.083
Cross-validation details (10-fold Crossvalidation)