Run
6023532

Run 6023532

Task 3561 (Supervised Classification) profb Uploaded 18-07-2017 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[3, 4, 7, 8]
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[3, 4, 7, 8]
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)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C16.337559461028
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.9342305068334071
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree1
sklearn.svm.classes.SVC(8)_gamma0.44374940867288304
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_state25558
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.041135143871085744
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
0.7615 ± 0.0687
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7082 ± 0.0525
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3248 ± 0.1225
Cross-validation details (10-fold Crossvalidation)
KB relative information score
125.5718 ± 3.5817
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3647 ± 0.0159
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4446 ± 0.0022
Cross-validation details (10-fold Crossvalidation)
Number of instances
672
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7341 ± 0.0523
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7381 ± 0.0397
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9188
Cross-validation details (10-fold Crossvalidation)
Recall
0.7381 ± 0.0397
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8202 ± 0.0367
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4251 ± 0.0213
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9018 ± 0.0468
Cross-validation details (10-fold Crossvalidation)