Run
9848067

Run 9848067

Task 34539 (Supervised Classification) Amazon_employee_access Uploaded 22-10-2018 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.imputation.Imputer(29)_missing_values"NaN"
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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)_C749.8794862096793
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sklearn.svm.classes.SVC(22)_class_weightnull
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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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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
0.5363 ± 0.0116
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9226 ± 0.0029
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1239 ± 0.0375
Cross-validation details (10-fold Crossvalidation)
KB relative information score
8604.1249 ± 70.8202
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0561 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1091 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
32769
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.928 ± 0.007
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9439 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3191
Cross-validation details (10-fold Crossvalidation)
Recall
0.9439 ± 0.0016
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5138 ± 0.0147
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2335 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2368 ± 0.0033
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0138 ± 0.0148
Cross-validation details (10-fold Crossvalidation)