Run
106028

Run 106028

Task 37 (Supervised Classification) breast-w Uploaded 17-08-2020 by Test Test
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  • openml-python Sklearn_0.23.1. study_14475
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Flow

sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.Col umnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._ base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEnco der),cont=sklearn.preprocessing._function_transformer.FunctionTransformer), estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGr adientBoostingClassifier)(2)Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting it to 'passthrough' or ``None``.
sklearn.impute._base.SimpleImputer(21)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(21)_copytrue
sklearn.impute._base.SimpleImputer(21)_fill_valuenull
sklearn.impute._base.SimpleImputer(21)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(21)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(21)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(15)_categories"auto"
sklearn.preprocessing._encoders.OneHotEncoder(15)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(15)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(15)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(15)_sparsefalse
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(4)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(4)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(4)_verbosefalse
sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer),estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer),estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "transform", "step_name": "transform"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer),estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(2)_verbosefalse
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(2)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(2)_remainder"drop"
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(2)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(2)_transformer_weightsnull
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(2)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": {"oml-python:serialized_object": "function", "value": "__main__.cat"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": {"oml-python:serialized_object": "function", "value": "__main__.cont"}}}]
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(2)_verbosefalse
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_accept_sparsefalse
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_check_inversetrue
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_func{"oml-python:serialized_object": "function", "value": "__main__."}
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_inverse_funcnull
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(2)_validatefalse
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_early_stopping"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_l2_regularization0.0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_learning_rate0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_loss"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_max_bins255
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_max_depthnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_max_iter100
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_max_leaf_nodes31
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_min_samples_leaf20
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_monotonic_cstnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_n_iter_no_change10
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_random_state25430
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_scoring"loss"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_tol1e-07
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_validation_fraction0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_verbose0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(3)_warm_startfalse

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.

18 Evaluation measures

0.9914 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
0.9571 ± 0.0188
Per class
Cross-validation details (10-fold Crossvalidation)
0.9052 ± 0.0409
Cross-validation details (10-fold Crossvalidation)
0.8936 ± 0.0389
Cross-validation details (10-fold Crossvalidation)
0.0472 ± 0.0167
Cross-validation details (10-fold Crossvalidation)
0.4519 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
0.9571 ± 0.019
Cross-validation details (10-fold Crossvalidation)
699
Per class
Cross-validation details (10-fold Crossvalidation)
0.9572 ± 0.0185
Per class
Cross-validation details (10-fold Crossvalidation)
0.9571 ± 0.019
Cross-validation details (10-fold Crossvalidation)
0.9293 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
0.1045 ± 0.0369
Cross-validation details (10-fold Crossvalidation)
0.4753 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
0.1916 ± 0.0386
Cross-validation details (10-fold Crossvalidation)
0.4031 ± 0.0811
Cross-validation details (10-fold Crossvalidation)
0.9535 ± 0.0174
Cross-validation details (10-fold Crossvalidation)