Run
3969

Run 3969

Task 109 (Supervised Classification) segment Uploaded 01-03-2021 by Test Test
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  • openml-python Sklearn_0.23.1. study_533
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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,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sk learn.preprocessing._function_transformer.FunctionTransformer),estimator=sk learn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoosti ngClassifier)(1)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.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer),estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer),estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)_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,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer),estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)_verbosefalse
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_remainder"drop"
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_transformer_weightsnull
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_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,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_verbosefalse
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD)(1)_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"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "truncatedsvd", "step_name": "truncatedsvd"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD)(1)_verbosefalse
sklearn.impute._base.SimpleImputer(7)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(7)_copytrue
sklearn.impute._base.SimpleImputer(7)_fill_valuenull
sklearn.impute._base.SimpleImputer(7)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(7)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(7)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(8)_categories"auto"
sklearn.preprocessing._encoders.OneHotEncoder(8)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(8)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(8)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(8)_sparsefalse
sklearn.decomposition._truncated_svd.TruncatedSVD(2)_algorithm"randomized"
sklearn.decomposition._truncated_svd.TruncatedSVD(2)_n_components2
sklearn.decomposition._truncated_svd.TruncatedSVD(2)_n_iter5
sklearn.decomposition._truncated_svd.TruncatedSVD(2)_random_state18425
sklearn.decomposition._truncated_svd.TruncatedSVD(2)_tol0.0
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_check_inversetrue
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_func{"oml-python:serialized_object": "function", "value": "__main__."}
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(1)_validatefalse
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_early_stopping"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_l2_regularization0.0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_learning_rate0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_loss"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_max_bins255
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_max_depthnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_max_iter100
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_max_leaf_nodes31
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_min_samples_leaf20
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_monotonic_cstnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_n_iter_no_change10
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_random_state208
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_scoring"loss"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_tol1e-07
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_validation_fraction0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_verbose0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(1)_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

Area under ROC curve
0.5629 ± 0.013
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2801 ± 0.0049
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1611 ± 0.0056
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.2247 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2054 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2449
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.281 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Number of instances
2310
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2793 ± 0.0066
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.281 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.8074
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8387 ± 0.005
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3499
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.452 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2916 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.281 ± 0.0048
Cross-validation details (10-fold Crossvalidation)