Run
10154565

Run 10154565

Task 23 (Supervised Classification) cmc 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
0.704 ± 0.0467
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.543 ± 0.064
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2944 ± 0.0972
Cross-validation details (10-fold Crossvalidation)
KB relative information score
319.1915 ± 5.465
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3653 ± 0.0138
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4308 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5567 ± 0.0666
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5506 ± 0.0608
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5392
Cross-validation details (10-fold Crossvalidation)
Recall
0.5506 ± 0.0608
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8478 ± 0.0322
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4641 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.432 ± 0.016
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9308 ± 0.0347
Cross-validation details (10-fold Crossvalidation)