Run
10154599

Run 10154599

Task 37 (Supervised Classification) diabetes 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_state3674
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
0.6682 ± 0.052
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6963 ± 0.0507
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.334 ± 0.107
Cross-validation details (10-fold Crossvalidation)
KB relative information score
231.9468 ± 9.5582
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3047 ± 0.0531
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4545 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Number of instances
768
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6975 ± 0.0476
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6953 ± 0.0531
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9335
Cross-validation details (10-fold Crossvalidation)
Recall
0.6953 ± 0.0531
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6704 ± 0.1178
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4766 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.552 ± 0.0484
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.1581 ± 0.1032
Cross-validation details (10-fold Crossvalidation)