Run
9656326

Run 9656326

Task 125923 (Supervised Classification) Australian 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
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sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C2.287172664078396
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sklearn.svm.classes.SVC(22)_gamma0.21313143968487494
sklearn.svm.classes.SVC(22)_kernel"rbf"
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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
sklearn.feature_selection.variance_threshold.VarianceThreshold(18)_threshold0.0
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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
0.8425 ± 0.0236
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8423 ± 0.0222
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6817 ± 0.0448
Cross-validation details (10-fold Crossvalidation)
KB relative information score
468.1223 ± 3.1124
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.158 ± 0.0221
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.494 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Number of instances
690
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8434 ± 0.0219
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.842 ± 0.0221
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9913
Cross-validation details (10-fold Crossvalidation)
Recall
0.842 ± 0.0221
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3198 ± 0.0447
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.497 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3975 ± 0.0285
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7998 ± 0.0575
Cross-validation details (10-fold Crossvalidation)