Run
8981510

Run 8981510

Task 125921 (Supervised Classification) LED-display-domain-7digit Uploaded 08-04-2018 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,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(2)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(5)_axis0
openmlstudy14.preprocessing.ConditionalImputer(5)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(9)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(7)_threshold0.0
sklearn.svm.classes.SVC(11)_C23744.586632811264
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef00.3581755136571494
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree2
sklearn.svm.classes.SVC(11)_gamma1.286556741185558e-05
sklearn.svm.classes.SVC(11)_kernel"rbf"
sklearn.svm.classes.SVC(11)_max_iter-1
sklearn.svm.classes.SVC(11)_probabilitytrue
sklearn.svm.classes.SVC(11)_random_state60561
sklearn.svm.classes.SVC(11)_shrinkingfalse
sklearn.svm.classes.SVC(11)_tol0.0007035830468109636
sklearn.svm.classes.SVC(11)_verbosefalse
sklearn.preprocessing.data.StandardScaler(7)_copytrue
sklearn.preprocessing.data.StandardScaler(7)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(7)_with_stdtrue

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
0.9423 ± 0.02
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7394 ± 0.0597
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7108 ± 0.0626
Cross-validation details (10-fold Crossvalidation)
KB relative information score
313.7764 ± 2.0925
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.096 ± 0.0067
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
0.743 ± 0.0535
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.74 ± 0.0566
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3127
Cross-validation details (10-fold Crossvalidation)
Recall
0.74 ± 0.0566
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5342 ± 0.0376
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
0.2042 ± 0.0141
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6812 ± 0.0472
Cross-validation details (10-fold Crossvalidation)