Run
10454042

Run 10454042

Task 53 (Supervised Classification) vehicle 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=sklearn.ensemble._weight_boosting.AdaBoost Classifier)(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(step_0=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(1)_verbosefalse
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_algorithm"SAMME"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_base_estimatornull
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_learning_rate0.0038349064562157777
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_n_estimators1092
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_random_state42

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

0.7729 ± 0.0219
Per class
Cross-validation details (10-fold Crossvalidation)
0.4926 ± 0.0375
Per class
Cross-validation details (10-fold Crossvalidation)
0.3737 ± 0.048
Cross-validation details (10-fold Crossvalidation)
0.0398 ± 0.002
Cross-validation details (10-fold Crossvalidation)
0.3689 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.3748 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5272 ± 0.0365
Cross-validation details (10-fold Crossvalidation)
846
Per class
Cross-validation details (10-fold Crossvalidation)
0.5993 ± 0.0596
Per class
Cross-validation details (10-fold Crossvalidation)
0.5272 ± 0.0365
Cross-validation details (10-fold Crossvalidation)
1.9991 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.9841 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
0.4329 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4262 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
0.9846 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
0.5349 ± 0.0378
Cross-validation details (10-fold Crossvalidation)