Run
10228018

Run 10228018

Task 14965 (Supervised Classification) bank-marketing Uploaded 08-05-2019 by joe zhou
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sk learn.tree.tree.DecisionTreeClassifier)(2)Automatically created scikit-learn flow.
sklearn.impute.SimpleImputer(10)_copytrue
sklearn.impute.SimpleImputer(10)_fill_valuenull
sklearn.impute.SimpleImputer(10)_missing_valuesNaN
sklearn.impute.SimpleImputer(10)_strategy"mean"
sklearn.impute.SimpleImputer(10)_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_state57268
sklearn.tree.tree.DecisionTreeClassifier(37)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_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
0.7062 ± 0.0147
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.876 ± 0.0053
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4051 ± 0.0267
Cross-validation details (10-fold Crossvalidation)
KB relative information score
9619.6899 ± 150.8443
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1251 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2066 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
45211
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8771 ± 0.0055
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8749 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5207
Cross-validation details (10-fold Crossvalidation)
Recall
0.8749 ± 0.0053
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6057 ± 0.0256
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3214 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3538 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.1007 ± 0.0234
Cross-validation details (10-fold Crossvalidation)