Run
5970616

Run 5970616

Task 2079 (Supervised Classification) eucalyptus 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[0, 2, 3, 4, 9]
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[0, 2, 3, 4, 9]
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)_C0.04468514539870221
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.3761196440510657
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree1
sklearn.svm.classes.SVC(8)_gamma0.00016096250602076395
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_state39961
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0064777630698174896
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
0.726 ± 0.0323
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.353
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2371 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
KB relative information score
103.4617 ± 1.2702
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2926 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3132 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
736
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.4425
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4361 ± 0.0189
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.2629
Cross-validation details (10-fold Crossvalidation)
Recall
0.4361 ± 0.0189
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9342 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3957 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3771 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.953 ± 0.0087
Cross-validation details (10-fold Crossvalidation)