Run
10461937

Run 10461937

Task 3891 (Supervised Classification) gina_agnostic 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.tr ee._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_alpha0.713480854555603
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth52
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features0.585800015030934
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes851
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.1719743428410835
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.42911995936636743
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.3526715754100773
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.041908331803751364
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.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=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"}}]
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=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

0.4987
Per class
Cross-validation details (10-fold Crossvalidation)
-0 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5084 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
3468
Per class
Cross-validation details (10-fold Crossvalidation)
0.5084 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
0.9998 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)