Run
9716090

Run 9716090

Task 21 (Supervised Classification) car 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._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C27338.842887738465
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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"
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
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
0.994 ± 0.0057
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9942 ± 0.0038
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9874 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1702.0647 ± 2.0785
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0029 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
1728
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9942 ± 0.0034
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9942 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2099
Cross-validation details (10-fold Crossvalidation)
Recall
0.9942 ± 0.0039
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0126 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0538 ± 0.0266
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.1591 ± 0.0789
Cross-validation details (10-fold Crossvalidation)