Run
6046648

Run 6046648

Task 125921 (Supervised Classification) LED-display-domain-7digit Uploaded 25-07-2017 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[]
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)_C0.07719640479017242
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma5.083946436573301
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state33335
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.004356611365653279
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
0.9075 ± 0.0241
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6562 ± 0.0824
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5993 ± 0.0954
Cross-validation details (10-fold Crossvalidation)
KB relative information score
234.6829 ± 3.0896
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1198 ± 0.0092
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1797 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7199 ± 0.0433
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.64 ± 0.0859
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3127
Cross-validation details (10-fold Crossvalidation)
Recall
0.64 ± 0.0859
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6665 ± 0.0511
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2998 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2298 ± 0.0148
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7665 ± 0.0495
Cross-validation details (10-fold Crossvalidation)