Run
2083594

Run 2083594

Task 47 (Supervised Classification) tae Uploaded 23-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.0. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1. Sun_Apr_23_23.18.24_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEn coder,extratreeclassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(3)_categorical_features[True, False, False, True, False]
sklearn.preprocessing.data.OneHotEncoder(3)_dtype
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknownignore
sklearn.preprocessing.data.OneHotEncoder(3)_n_valuesauto
sklearn.preprocessing.data.OneHotEncoder(3)_sparseFalse
sklearn.tree.tree.ExtraTreeClassifier(1)_class_weightNone
sklearn.tree.tree.ExtraTreeClassifier(1)_criterionentropy
sklearn.tree.tree.ExtraTreeClassifier(1)_max_depthNone
sklearn.tree.tree.ExtraTreeClassifier(1)_max_features0.7
sklearn.tree.tree.ExtraTreeClassifier(1)_max_leaf_nodesNone
sklearn.tree.tree.ExtraTreeClassifier(1)_min_impurity_split1e-07
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_leaf1
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_split2
sklearn.tree.tree.ExtraTreeClassifier(1)_min_weight_fraction_leaf0.0
sklearn.tree.tree.ExtraTreeClassifier(1)_random_state3
sklearn.tree.tree.ExtraTreeClassifier(1)_splitterrandom
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEncoder,extratreeclassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)_steps[('onehotencoder', OneHotEncoder(categorical_features=[True, False, False, True, False], dtype=, handle_unknown='ignore', n_values='auto', sparse=False)), ('extratreeclassifier', ExtraTreeClassifier(class_weight=None, criterion='entropy', max_depth=None, max_features=0.7, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, random_state=3, splitter='random'))]

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
0.8086
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7142
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5727
Cross-validation details (10-fold Crossvalidation)
KB relative information score
94.3403
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1825
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4443
Cross-validation details (10-fold Crossvalidation)
Number of instances
151
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7144
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7152
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5845
Cross-validation details (10-fold Crossvalidation)
Recall
0.7152
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4107
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4713
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4163
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8832
Cross-validation details (10-fold Crossvalidation)