Run
9638075

Run 9638075

Task 9980 (Supervised Classification) climate-model-simulation-crashes Uploaded 20-10-2018 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.imputation.Imputer(29)_copytrue
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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)_C2819.597367758444
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sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef0-0.015063047971368482
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sklearn.svm.classes.SVC(22)_gamma0.06154873414464932
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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"
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)_sparse_threshold0.3
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
0.5814 ± 0.0892
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8775 ± 0.0208
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1786 ± 0.1347
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-8.3825 ± 13.471
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1167 ± 0.0303
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
0.8724 ± 0.0268
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8833 ± 0.0303
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.4254
Cross-validation details (10-fold Crossvalidation)
Recall
0.8833 ± 0.0303
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7425 ± 0.1861
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
0.3416 ± 0.0442
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2235 ± 0.1532
Cross-validation details (10-fold Crossvalidation)