Run
6045845

Run 6045845

Task 21 (Supervised Classification) car 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[0, 1, 2, 3, 4, 5]
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[0, 1, 2, 3, 4, 5]
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)_C0.7289609726218871
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.5100425408460834
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree5
sklearn.svm.classes.SVC(8)_gamma0.026568087118093567
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_state64473
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.0006617268026997811
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
0.9512 ± 0.009
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8337 ± 0.0276
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6546 ± 0.0607
Cross-validation details (10-fold Crossvalidation)
KB relative information score
969.6928 ± 5.9081
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1148 ± 0.0068
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
1728
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8371 ± 0.0262
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8368 ± 0.0309
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2099
Cross-validation details (10-fold Crossvalidation)
Recall
0.8368 ± 0.0309
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5011 ± 0.0305
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.241 ± 0.014
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7127 ± 0.0424
Cross-validation details (10-fold Crossvalidation)