Run
6056237

Run 6056237

Task 125921 (Supervised Classification) LED-display-domain-7digit Uploaded 28-07-2017 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"most_frequent"
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)_C0.29227489893969066
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.8437184127573905
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree5
sklearn.svm.classes.SVC(8)_gamma0.5410553318734478
sklearn.svm.classes.SVC(8)_kernel"poly"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state60827
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol2.93695592143026e-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
0.9269 ± 0.0202
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6866 ± 0.0633
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6491 ± 0.0736
Cross-validation details (10-fold Crossvalidation)
KB relative information score
268.9722 ± 2.4234
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1165 ± 0.0072
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
0.7032 ± 0.0406
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.684 ± 0.0672
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3127
Cross-validation details (10-fold Crossvalidation)
Recall
0.684 ± 0.0672
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6479 ± 0.0402
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
0.2228 ± 0.0141
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7432 ± 0.047
Cross-validation details (10-fold Crossvalidation)