Run
6142506

Run 6142506

Task 9986 (Supervised Classification) gas-drift Uploaded 26-08-2017 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"mean"
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)_C4725.366016905572
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.3916918118130799
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma8.737417057393507e-05
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_state58104
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.001274526509938201
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
0.4987 ± 0.0751
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.0577
Per class
Kappa
-0.1494 ± 0.147
Cross-validation details (10-fold Crossvalidation)
KB relative information score
184.5905 ± 9.1263
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2735 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2748 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
13910
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2061
Per class
Predictive accuracy
0.0948 ± 0.1163
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5457
Cross-validation details (10-fold Crossvalidation)
Recall
0.0948 ± 0.1163
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9954 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3707 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.37 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9983 ± 0.0022
Cross-validation details (10-fold Crossvalidation)