Run
4569739

Run 4569739

Task 2 (Supervised Classification) anneal Uploaded 07-07-2017 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)(2)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(6)_categorical_features[0, 1, 2, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 35, 36, 37]
sklearn.preprocessing.data.OneHotEncoder(6)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(6)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(6)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(6)_sparsefalse
openmlstudy14.preprocessing.ConditionalImputer(3)_axis0
openmlstudy14.preprocessing.ConditionalImputer(3)_categorical_features[0, 1, 2, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 35, 36, 37]
openmlstudy14.preprocessing.ConditionalImputer(3)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(3)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(3)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(3)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(3)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(3)_verbose0
sklearn.feature_selection.variance_threshold.VarianceThreshold(5)_threshold0.0
sklearn.svm.classes.SVC(9)_C16881.410228971028
sklearn.svm.classes.SVC(9)_cache_size200
sklearn.svm.classes.SVC(9)_class_weightnull
sklearn.svm.classes.SVC(9)_coef00.0
sklearn.svm.classes.SVC(9)_decision_function_shapenull
sklearn.svm.classes.SVC(9)_degree3
sklearn.svm.classes.SVC(9)_gamma0.0001735310057996855
sklearn.svm.classes.SVC(9)_kernel"rbf"
sklearn.svm.classes.SVC(9)_max_iter-1
sklearn.svm.classes.SVC(9)_probabilitytrue
sklearn.svm.classes.SVC(9)_random_state33783
sklearn.svm.classes.SVC(9)_shrinkingfalse
sklearn.svm.classes.SVC(9)_tol6.548544330076311e-05
sklearn.svm.classes.SVC(9)_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
0.8629
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8392
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5815
Cross-validation details (10-fold Crossvalidation)
KB relative information score
396.3648
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0834
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1343
Cross-validation details (10-fold Crossvalidation)
Number of instances
898
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8367
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8519
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2149
Cross-validation details (10-fold Crossvalidation)
Recall
0.8519
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6208
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2582
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2035
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7883
Cross-validation details (10-fold Crossvalidation)