Run
2012947

Run 2012947

Task 23 (Supervised Classification) cmc Uploaded 07-04-2017 by Jeroen van Hoof
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  • Fri_Apr__7_02.43.29_2017 NumPy_1.12.1. Python_3.5.3. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,oneho tencoder=sklearn.preprocessing.data.OneHotEncoder,decisiontreeclassifier=sk learn.tree.tree.DecisionTreeClassifier)(1)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(6)_class_weightNone
sklearn.tree.tree.DecisionTreeClassifier(6)_criteriongini
sklearn.tree.tree.DecisionTreeClassifier(6)_max_depthNone
sklearn.tree.tree.DecisionTreeClassifier(6)_max_featuresNone
sklearn.tree.tree.DecisionTreeClassifier(6)_max_leaf_nodesNone
sklearn.tree.tree.DecisionTreeClassifier(6)_min_impurity_split1e-07
sklearn.tree.tree.DecisionTreeClassifier(6)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(6)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(6)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(6)_presortFalse
sklearn.tree.tree.DecisionTreeClassifier(6)_random_stateNone
sklearn.tree.tree.DecisionTreeClassifier(6)_splitterbest
sklearn.preprocessing.data.OneHotEncoder(3)_categorical_features[False, True, True, False, True, True, True, True, True]
sklearn.preprocessing.data.OneHotEncoder(3)_dtype
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknownerror
sklearn.preprocessing.data.OneHotEncoder(3)_n_valuesauto
sklearn.preprocessing.data.OneHotEncoder(3)_sparseTrue
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1)_steps[('dualimputer', ), ('onehotencoder', OneHotEncoder(categorical_features=[False, True, True, False, True, True, True, True, True], dtype=, handle_unknown='error', n_values='auto', sparse=True)), ('decisiontreeclassifier', DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None, max_features=None, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, presort=False, random_state=None, splitter='best'))]

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
0.609
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4848
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2023
Cross-validation details (10-fold Crossvalidation)
KB relative information score
392.9791
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3422
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4308
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.4837
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4861
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5392
Cross-validation details (10-fold Crossvalidation)
Recall
0.4861
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7942
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4641
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.578
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2455
Cross-validation details (10-fold Crossvalidation)