Run
9702017

Run 9702017

Task 3543 (Supervised Classification) irish 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.data.StandardScaler(14)_with_stdtrue
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sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C28.983134619828892
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sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef0-0.5653208834068861
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sklearn.svm.classes.SVC(22)_degree3
sklearn.svm.classes.SVC(22)_gamma0.1334164091922344
sklearn.svm.classes.SVC(22)_kernel"sigmoid"
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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
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)_transformer_weightsnull
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
0.9838 ± 0.0188
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.984 ± 0.0184
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9676 ± 0.0373
Cross-validation details (10-fold Crossvalidation)
KB relative information score
483.6725 ± 1.8998
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.016 ± 0.0184
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4938 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.984 ± 0.0175
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.984 ± 0.0184
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.991
Cross-validation details (10-fold Crossvalidation)
Recall
0.984 ± 0.0184
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0324 ± 0.0373
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4969 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1265 ± 0.0955
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2546 ± 0.1923
Cross-validation details (10-fold Crossvalidation)