Run
10154556

Run 10154556

Task 11 (Supervised Classification) balance-scale 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_depth4
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_state60416
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
0.8491 ± 0.034
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7654 ± 0.0184
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6173 ± 0.0619
Cross-validation details (10-fold Crossvalidation)
KB relative information score
293.4455 ± 2.5874
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.203 ± 0.0191
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3798 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Number of instances
625
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7479 ± 0.0104
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.792 ± 0.0354
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.3212
Cross-validation details (10-fold Crossvalidation)
Recall
0.792 ± 0.0354
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5345 ± 0.0499
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4356 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3373 ± 0.0235
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7744 ± 0.0531
Cross-validation details (10-fold Crossvalidation)