Run
9807357

Run 9807357

Task 9980 (Supervised Classification) climate-model-simulation-crashes Uploaded 22-10-2018 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)_C57.05377906782048
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sklearn.svm.classes.SVC(22)_coef00.8014903734972039
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sklearn.svm.classes.SVC(22)_gamma3.6623260626599534
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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
0.5083 ± 0.0474
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8609 ± 0.0167
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0205 ± 0.1038
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-42.7814 ± 11.7587
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1241 ± 0.0263
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
0.8476 ± 0.024
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8759 ± 0.0263
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.4254
Cross-validation details (10-fold Crossvalidation)
Recall
0.8759 ± 0.0263
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7896 ± 0.1672
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
0.3522 ± 0.0391
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2618 ± 0.1413
Cross-validation details (10-fold Crossvalidation)