Run
9706948

Run 9706948

Task 9983 (Supervised Classification) eeg-eye-state 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.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
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sklearn.svm.classes.SVC(22)_C571.0235113854529
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sklearn.svm.classes.SVC(22)_gamma0.4892796960263618
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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
0.89 ± 0.0263
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8919 ± 0.0259
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7814 ± 0.0524
Cross-validation details (10-fold Crossvalidation)
KB relative information score
11696.5096 ± 78.5726
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1079 ± 0.0258
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4948 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
14980
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.892 ± 0.0259
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8921 ± 0.0258
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9924
Cross-validation details (10-fold Crossvalidation)
Recall
0.8921 ± 0.0258
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2182 ± 0.0522
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4974 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3285 ± 0.0432
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6606 ± 0.0869
Cross-validation details (10-fold Crossvalidation)