Run
8818410

Run 8818410

Task 125921 (Supervised Classification) LED-display-domain-7digit Uploaded 24-01-2018 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.preprocessing.data.StandardScaler(6)_copytrue
sklearn.preprocessing.data.StandardScaler(6)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(6)_with_stdtrue
sklearn.svm.classes.SVC(17)_C210.19562795624003
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.6558065842004441
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree3
sklearn.svm.classes.SVC(17)_gamma0.010617140927448986
sklearn.svm.classes.SVC(17)_kernel"sigmoid"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state57361
sklearn.svm.classes.SVC(17)_shrinkingfalse
sklearn.svm.classes.SVC(17)_tol2.633461411420124e-05
sklearn.svm.classes.SVC(17)_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
0.9394 ± 0.0144
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7208 ± 0.06
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6906 ± 0.0638
Cross-validation details (10-fold Crossvalidation)
KB relative information score
308.5998 ± 2.0588
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0986 ± 0.007
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
0.7221 ± 0.0572
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.722 ± 0.0577
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3127
Cross-validation details (10-fold Crossvalidation)
Recall
0.722 ± 0.0577
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5487 ± 0.0389
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
0.2077 ± 0.0134
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6929 ± 0.0447
Cross-validation details (10-fold Crossvalidation)