Run
10389726

Run 10389726

Task 3022 (Supervised Classification) vowel Uploaded 27-08-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardSc aler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),svc=sklea rn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(30)_copytrue
sklearn.preprocessing.data.StandardScaler(30)_with_meantrue
sklearn.preprocessing.data.StandardScaler(30)_with_stdtrue
sklearn.svm.classes.SVC(32)_C1.0
sklearn.svm.classes.SVC(32)_cache_size200
sklearn.svm.classes.SVC(32)_class_weightnull
sklearn.svm.classes.SVC(32)_coef00.0
sklearn.svm.classes.SVC(32)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(32)_degree3
sklearn.svm.classes.SVC(32)_gamma"scale"
sklearn.svm.classes.SVC(32)_kernel"rbf"
sklearn.svm.classes.SVC(32)_max_iter-1
sklearn.svm.classes.SVC(32)_probabilityfalse
sklearn.svm.classes.SVC(32)_random_state3
sklearn.svm.classes.SVC(32)_shrinkingtrue
sklearn.svm.classes.SVC(32)_tol0.001
sklearn.svm.classes.SVC(32)_verbosefalse
sklearn.preprocessing._encoders.OneHotEncoder(12)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(12)_handle_unknown"error"
sklearn.preprocessing._encoders.OneHotEncoder(12)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_sparsetrue
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),svc=sklearn.svm.classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),svc=sklearn.svm.classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),svc=sklearn.svm.classes.SVC)(1)_verbosefalse
sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_remainder"drop"
sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_transformer_weightsnull
sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler", "argument_1": [true, true, false, false, false, false, false, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": [true, true, false, false, false, false, false, false, false, false, false, false]}}]
sklearn.compose._column_transformer.ColumnTransformer(standardscaler=sklearn.preprocessing.data.StandardScaler,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbosefalse

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

0.4511 ± 0.0023
Per class
Cross-validation details (10-fold Crossvalidation)
0.0018
Per class
-0.0978 ± 0.0047
Cross-validation details (10-fold Crossvalidation)
-0.0376 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
0.1815 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.1653
Cross-validation details (10-fold Crossvalidation)
990
Per class
Cross-validation details (10-fold Crossvalidation)
0.0017
Per class
0.002 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
3.4594
Cross-validation details (10-fold Crossvalidation)
0.002 ± 0.0043
Per class
Cross-validation details (10-fold Crossvalidation)
1.0978 ± 0.0047
Cross-validation details (10-fold Crossvalidation)
0.2875
Cross-validation details (10-fold Crossvalidation)
0.426 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
1.4817 ± 0.0032
Cross-validation details (10-fold Crossvalidation)