Run
5994752

Run 5994752

Task 219 (Supervised Classification) electricity Uploaded 17-07-2017 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[1]
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[1]
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)_C3133.0539932186625
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.8695082112859001
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma5.4496760448324
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_state11676
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.008431005310384812
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
0.4186 ± 0.1131
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4161 ± 0.0443
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.1501 ± 0.1075
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-2072.1806 ± 195.3803
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5039 ± 0.0165
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4886 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
45312
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.4 ± 0.0756
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4836 ± 0.0563
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9835
Cross-validation details (10-fold Crossvalidation)
Recall
0.4836 ± 0.0563
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0313 ± 0.0338
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4943 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5101 ± 0.0132
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0319 ± 0.0267
Cross-validation details (10-fold Crossvalidation)