Run
9653370

Run 9653370

Task 3560 (Supervised Classification) analcatdata_dmft 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
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sklearn.svm.classes.SVC(22)_C598.390687134531
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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
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
0.5142 ± 0.0241
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.184 ± 0.0407
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0289 ± 0.048
Cross-validation details (10-fold Crossvalidation)
KB relative information score
87.5914 ± 3.5666
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2689 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2774 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
797
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.1865 ± 0.0564
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.1932 ± 0.0407
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5803
Cross-validation details (10-fold Crossvalidation)
Recall
0.1932 ± 0.0407
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9694 ± 0.0489
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3724 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5186 ± 0.013
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.3924 ± 0.035
Cross-validation details (10-fold Crossvalidation)