Run
10154577

Run 10154577

Task 53 (Supervised Classification) vehicle 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
0.8808 ± 0.0281
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6686 ± 0.0379
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.568 ± 0.0514
Cross-validation details (10-fold Crossvalidation)
KB relative information score
503.1637 ± 3.4332
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.186 ± 0.0145
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3748 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
846
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6641 ± 0.0514
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6761 ± 0.0384
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.9991
Cross-validation details (10-fold Crossvalidation)
Recall
0.6761 ± 0.0384
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4962 ± 0.0387
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4329 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3188 ± 0.02
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7363 ± 0.046
Cross-validation details (10-fold Crossvalidation)