Run
6015371

Run 6015371

Task 3021 (Supervised Classification) sick Uploaded 18-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=skle arn.tree.tree.DecisionTreeClassifier))(1)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(10)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(10)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(10)_max_depth4
sklearn.tree.tree.DecisionTreeClassifier(10)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(10)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(10)_min_impurity_split1e-07
sklearn.tree.tree.DecisionTreeClassifier(10)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(10)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(10)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(10)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(10)_random_state11602
sklearn.tree.tree.DecisionTreeClassifier(10)_splitter"best"
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 24, 26, 28]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 24, 26, 28]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_algorithm"SAMME"
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_learning_rate0.38768484189620345
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_n_estimators84
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_random_state29781

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
0.9966 ± 0.0028
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9896 ± 0.0063
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9084 ± 0.0556
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-23723.0732 ± 24.8151
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3412 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1152 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Number of instances
3772
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9895 ± 0.0062
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9897 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3333
Cross-validation details (10-fold Crossvalidation)
Recall
0.9897 ± 0.0062
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
2.9625 ± 0.0444
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2398 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3436 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.433 ± 0.0207
Cross-validation details (10-fold Crossvalidation)