Run
10453722

Run 10453722

Task 146821 (Supervised Classification) car Uploaded 18-05-2020 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.on e_hot_encoding.OneHotEncoderComponent,step_1=sklearn.tree._classes.Decision TreeClassifier)(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_alpha0.04960015520534877
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth14
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features0.8351621719174466
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes359
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.12538001435875581
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.08934010670216806
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.057282191991121625
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.3562947383316801
sklearn.tree._classes.DecisionTreeClassifier(3)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter"random"
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,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.one_hot_encoding.OneHotEncoderComponent,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

0.497
Per class
Cross-validation details (10-fold Crossvalidation)
0.0013 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.2286 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.7002 ± 0.0017
Cross-validation details (10-fold Crossvalidation)
1728
Per class
Cross-validation details (10-fold Crossvalidation)
0.7002 ± 0.0017
Cross-validation details (10-fold Crossvalidation)
1.2058 ± 0.0088
Cross-validation details (10-fold Crossvalidation)
0.9985 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.25
Cross-validation details (10-fold Crossvalidation)