Run
2339754

Run 2339754

Task 49 (Supervised Classification) tic-tac-toe Uploaded 24-05-2017 by Jeroen van Hoof
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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, true, true, true, true, true, true, true, true]
sklearn.preprocessing.data.OneHotEncoder(3)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(3)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(3)_sparsefalse
sklearn.tree.tree.ExtraTreeClassifier(1)_class_weightnull
sklearn.tree.tree.ExtraTreeClassifier(1)_criterion"gini"
sklearn.tree.tree.ExtraTreeClassifier(1)_max_depthnull
sklearn.tree.tree.ExtraTreeClassifier(1)_max_features0.8
sklearn.tree.tree.ExtraTreeClassifier(1)_max_leaf_nodesnull
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_state10
sklearn.tree.tree.ExtraTreeClassifier(1)_splitter"random"
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEncoder,extratreeclassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "extratreeclassifier", "step_name": "extratreeclassifier"}}]

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
0.947 ± 0.0214
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.952 ± 0.0204
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.894 ± 0.0445
Cross-validation details (10-fold Crossvalidation)
KB relative information score
851.8891 ± 4.7342
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.048 ± 0.0205
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.453 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Number of instances
958
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.952 ± 0.0202
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.952 ± 0.0205
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9312
Cross-validation details (10-fold Crossvalidation)
Recall
0.952 ± 0.0205
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.106 ± 0.0453
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4759 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2191 ± 0.0495
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4605 ± 0.1039
Cross-validation details (10-fold Crossvalidation)