Run
9627672

Run 9627672

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.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)_C0.7477590337787101
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sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef00.6643465933944683
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sklearn.svm.classes.SVC(22)_gamma0.12567687815726006
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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
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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
0.5581 ± 0.0825
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.89 ± 0.0234
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1723 ± 0.2031
Cross-validation details (10-fold Crossvalidation)
KB relative information score
129.2132 ± 7.4107
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.087 ± 0.0152
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
0.8847 ± 0.0294
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.913 ± 0.0152
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.4254
Cross-validation details (10-fold Crossvalidation)
Recall
0.913 ± 0.0152
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5539 ± 0.0966
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
0.295 ± 0.0254
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0568 ± 0.0965
Cross-validation details (10-fold Crossvalidation)