Run
5974258

Run 5974258

Task 37 (Supervised Classification) diabetes Uploaded 16-07-2017 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.svm.classes.SVC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[]
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.svm.classes.SVC(8)_C1.3482564996631516
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.7747695941215811
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree1
sklearn.svm.classes.SVC(8)_gamma0.005450737645766552
sklearn.svm.classes.SVC(8)_kernel"poly"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state843
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.003590030566139526
sklearn.svm.classes.SVC(8)_verbosefalse

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
0.8244 ± 0.0598
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7609 ± 0.0604
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4639 ± 0.138
Cross-validation details (10-fold Crossvalidation)
KB relative information score
239.4914 ± 4.691
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3198 ± 0.0205
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4545 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Number of instances
768
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7626 ± 0.0627
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7682 ± 0.0578
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9335
Cross-validation details (10-fold Crossvalidation)
Recall
0.7682 ± 0.0578
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7036 ± 0.0455
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4766 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3987 ± 0.0313
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8366 ± 0.0665
Cross-validation details (10-fold Crossvalidation)