Run
10461630

Run 10461630

Task 9899 (Supervised Classification) bank-marketing Uploaded 20-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
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Flow

sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.mu lti_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.fe ature_selection._variance_threshold.VarianceThreshold,step_2=sklearn.tree._ classes.DecisionTreeClassifier)(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.tree._classes.DecisionTreeClassifier(3)_ccp_alpha0.11529884106509125
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth15
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features0.675691173314054
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes1739
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.1944961970251604
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.4227465472488152
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.33671244386319615
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.06139077079560851
sklearn.tree._classes.DecisionTreeClassifier(3)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter"best"
automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent(1)_columnsnull
sklearn.feature_selection._variance_threshold.VarianceThreshold(2)_threshold0.0
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.feature_selection._variance_threshold.VarianceThreshold,step_2=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.feature_selection._variance_threshold.VarianceThreshold,step_2=sklearn.tree._classes.DecisionTreeClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_2", "step_name": "step_2"}}]
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.feature_selection._variance_threshold.VarianceThreshold,step_2=sklearn.tree._classes.DecisionTreeClassifier)(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.

16 Evaluation measures

0.4991
Per class
Cross-validation details (10-fold Crossvalidation)
0.0004 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.2039 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.2041 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
0.8848 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
4521
Per class
Cross-validation details (10-fold Crossvalidation)
0.8848 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.5155 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
0.9994 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.3193 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
0.3193 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)