Run
9709974

Run 9709974

Task 9980 (Supervised Classification) climate-model-simulation-crashes Uploaded 21-10-2018 by Scikit-learn Bot
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.pr eprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.St andardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.imput e.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder )),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceT hreshold,svc=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
sklearn.preprocessing.data.StandardScaler(14)_with_stdtrue
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sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C3.368987478779258
sklearn.svm.classes.SVC(22)_cache_size200
sklearn.svm.classes.SVC(22)_class_weightnull
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sklearn.svm.classes.SVC(22)_gamma0.0760000786415881
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sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_remainder"passthrough"
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sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_transformer_weightsnull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
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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
0.525 ± 0.0828
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8614 ± 0.0183
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0567 ± 0.1704
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-68.5805 ± 13.8952
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1296 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1571 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
Number of instances
540
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8532 ± 0.029
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8704 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.4254
Cross-validation details (10-fold Crossvalidation)
Recall
0.8704 ± 0.0231
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.825 ± 0.1819
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2792 ± 0.0143
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.36 ± 0.0319
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2897 ± 0.1701
Cross-validation details (10-fold Crossvalidation)