Run
6042180

Run 6042180

Task 36 (Supervised Classification) segment Uploaded 22-07-2017 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"mean"
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)_C249.70772742880126
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.7752172080481976
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree4
sklearn.svm.classes.SVC(8)_gamma5.45519119797053e-05
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_state58839
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.019292222855004107
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
0.9116 ± 0.0121
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6682 ± 0.0302
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6005 ± 0.0368
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1336.394 ± 8.0144
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1333 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2449
Cross-validation details (10-fold Crossvalidation)
Number of instances
2310
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.693 ± 0.0368
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6576 ± 0.0315
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.8074
Cross-validation details (10-fold Crossvalidation)
Recall
0.6576 ± 0.0315
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5443 ± 0.0416
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3499
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2507 ± 0.0108
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7164 ± 0.0309
Cross-validation details (10-fold Crossvalidation)