Run
9706381

Run 9706381

Task 34539 (Supervised Classification) Amazon_employee_access 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)_n_valuesnull
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sklearn.svm.classes.SVC(22)_C39.574049325515986
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sklearn.svm.classes.SVC(22)_class_weightnull
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sklearn.svm.classes.SVC(22)_gamma0.5582435471207327
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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
0.6679 ± 0.0154
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.945 ± 0.0029
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4342 ± 0.0335
Cross-validation details (10-fold Crossvalidation)
KB relative information score
12193.6554 ± 94.1885
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0477 ± 0.0022
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
0.9441 ± 0.0033
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9523 ± 0.0022
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3191
Cross-validation details (10-fold Crossvalidation)
Recall
0.9523 ± 0.0022
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4375 ± 0.02
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
0.2185 ± 0.005
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9355 ± 0.0214
Cross-validation details (10-fold Crossvalidation)