Run
5899526

Run 5899526

Task 3567 (Supervised Classification) collins Uploaded 13-07-2017 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[19, 20]
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[19, 20]
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)_C6260.299456648006
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.01119983419336741
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state61458
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0002431918228749029
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
0.9983 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9654 ± 0.0416
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9626 ± 0.0328
Cross-validation details (10-fold Crossvalidation)
KB relative information score
414.5075 ± 1.4783
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0385 ± 0.0034
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1212 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9667 ± 0.0306
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.966 ± 0.0299
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.6642
Cross-validation details (10-fold Crossvalidation)
Recall
0.966 ± 0.0299
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3176 ± 0.0282
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.246 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.099 ± 0.0094
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4022 ± 0.0387
Cross-validation details (10-fold Crossvalidation)