Run
9693283

Run 9693283

Task 34538 (Supervised Classification) MiceProtein 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.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)_C26.497232062467607
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sklearn.svm.classes.SVC(22)_coef00.0
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sklearn.svm.classes.SVC(22)_degree3
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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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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
0.9979 ± 0.0051
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9963 ± 0.0089
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9958 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1075.8241 ± 0.9807
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0009 ± 0.0022
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2185 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
1080
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9963 ± 0.008
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9963 ± 0.0089
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.9931
Cross-validation details (10-fold Crossvalidation)
Recall
0.9963 ± 0.0089
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0042 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3305 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0304 ± 0.0289
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.0921 ± 0.0875
Cross-validation details (10-fold Crossvalidation)