OpenML
6252667

Run 6252667

Task 2074 (Supervised Classification) satimage Uploaded 28-08-2017 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)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C43.33834617312941
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.02851560066029335
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.00046030517899537185
sklearn.svm.classes.SVC(8)_kernel"sigmoid"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state5230
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.0108784106242046
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
0.9816 ± 0.0043
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.856 ± 0.0164
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8281 ± 0.0205
Cross-validation details (10-fold Crossvalidation)
KB relative information score
5280.885 ± 9.4391
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0646 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2701 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
6430
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8537 ± 0.0169
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8614 ± 0.0165
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.4836
Cross-validation details (10-fold Crossvalidation)
Recall
0.8614 ± 0.0165
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2392 ± 0.013
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3675 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1784 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4855 ± 0.026
Cross-validation details (10-fold Crossvalidation)