Run
10154616

Run 10154616

Task 31 (Supervised Classification) credit-g Uploaded 06-02-2019 by Sarim Zafar
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,decisi ontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(33)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(33)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(33)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(33)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(33)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(33)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(33)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(33)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(33)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(33)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(33)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(33)_random_state13758
sklearn.tree.tree.DecisionTreeClassifier(33)_splitter"best"
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.impute.SimpleImputer(7)_copytrue
sklearn.impute.SimpleImputer(7)_fill_valuenull
sklearn.impute.SimpleImputer(7)_missing_valuesNaN
sklearn.impute.SimpleImputer(7)_strategy"mean"
sklearn.impute.SimpleImputer(7)_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
0.6471 ± 0.0449
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6945 ± 0.0325
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2851 ± 0.0794
Cross-validation details (10-fold Crossvalidation)
KB relative information score
208.2769 ± 8.5072
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.31 ± 0.0333
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
0.7005 ± 0.0348
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.69 ± 0.0333
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.69 ± 0.0333
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7378 ± 0.0793
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5568 ± 0.0293
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.215 ± 0.064
Cross-validation details (10-fold Crossvalidation)