Run
9707174

Run 9707174

Task 14964 (Supervised Classification) artificial-characters 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.imputation.Imputer(29)_missing_values"NaN"
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sklearn.preprocessing.imputation.Imputer(29)_verbose0
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sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
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sklearn.impute.SimpleImputer(1)_fill_value-1
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sklearn.impute.SimpleImputer(1)_strategy"constant"
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sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C607.5801883344841
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sklearn.svm.classes.SVC(22)_gamma0.0468143223740282
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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.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
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sklearn.pipeline.Pipeline(columntransformer=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)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,svc=sklearn.svm.classes.SVC)(1)_memorynull

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
0.8277 ± 0.0066
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6908 ± 0.0111
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6543 ± 0.0132
Cross-validation details (10-fold Crossvalidation)
KB relative information score
6892.379 ± 12.7946
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.062 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.179 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
10218
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7066 ± 0.0126
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6901 ± 0.0119
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.2849
Cross-validation details (10-fold Crossvalidation)
Recall
0.6901 ± 0.0119
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3463 ± 0.0133
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2992 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.249 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8322 ± 0.016
Cross-validation details (10-fold Crossvalidation)