Run
5981873

Run 5981873

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"most_frequent"
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)_C2703.4267876908916
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.05835012129116324
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.0022203676955618893
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_state22425
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol3.251119983573915e-05
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
0.8288 ± 0.0078
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7606 ± 0.0064
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5072 ± 0.0132
Cross-validation details (10-fold Crossvalidation)
KB relative information score
16308.309 ± 42.6699
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3266 ± 0.0041
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
0.7654 ± 0.0062
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7648 ± 0.0061
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9835
Cross-validation details (10-fold Crossvalidation)
Recall
0.7648 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6685 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4943 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4038 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8169 ± 0.0098
Cross-validation details (10-fold Crossvalidation)