Run
9863751

Run 9863751

Task 9986 (Supervised Classification) gas-drift Uploaded 23-10-2018 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)_C685.9828098554049
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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
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
0.9359 ± 0.0053
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9052 ± 0.0076
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8774 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
KB relative information score
12318.2977 ± 13.4528
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0335 ± 0.0028
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2748 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
13910
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9312 ± 0.0038
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8996 ± 0.0083
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5457
Cross-validation details (10-fold Crossvalidation)
Recall
0.8996 ± 0.0083
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1218 ± 0.01
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3707 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.183 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4936 ± 0.0203
Cross-validation details (10-fold Crossvalidation)