Run
8963024

Run 8963024

Task 9978 (Supervised Classification) ozone-level-8hr Uploaded 07-04-2018 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,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(2)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(5)_axis0
openmlstudy14.preprocessing.ConditionalImputer(5)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(9)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(7)_threshold0.0
sklearn.svm.classes.SVC(11)_C1.7104168368112265
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef0-0.39217083011830844
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree5
sklearn.svm.classes.SVC(11)_gamma0.00012163949943194653
sklearn.svm.classes.SVC(11)_kernel"rbf"
sklearn.svm.classes.SVC(11)_max_iter-1
sklearn.svm.classes.SVC(11)_probabilitytrue
sklearn.svm.classes.SVC(11)_random_state65406
sklearn.svm.classes.SVC(11)_shrinkingfalse
sklearn.svm.classes.SVC(11)_tol9.85343167064644e-05
sklearn.svm.classes.SVC(11)_verbosefalse
sklearn.preprocessing.data.StandardScaler(7)_copytrue
sklearn.preprocessing.data.StandardScaler(7)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(7)_with_stdtrue

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
0.9123 ± 0.031
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9159 ± 0.0064
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1236 ± 0.1001
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-501.1172 ± 19.3622
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0939 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1186 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
2534
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9238 ± 0.0137
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9392 ± 0.0034
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3411
Cross-validation details (10-fold Crossvalidation)
Recall
0.9392 ± 0.0034
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7919 ± 0.0207
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2432 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2115 ± 0.0082
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8696 ± 0.0332
Cross-validation details (10-fold Crossvalidation)