Run
10453471

Run 10453471

Task 9946 (Supervised Classification) wdbc 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_rate8.696718795910011e-06
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_n_estimators679
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

0.8716 ± 0.0572
Per class
Cross-validation details (10-fold Crossvalidation)
0.8877 ± 0.0449
Per class
Cross-validation details (10-fold Crossvalidation)
0.7574 ± 0.0972
Cross-validation details (10-fold Crossvalidation)
0.3863 ± 0.0538
Cross-validation details (10-fold Crossvalidation)
0.3204 ± 0.0197
Cross-validation details (10-fold Crossvalidation)
0.4676 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.8893 ± 0.0437
Cross-validation details (10-fold Crossvalidation)
569
Per class
Cross-validation details (10-fold Crossvalidation)
0.8899 ± 0.0429
Per class
Cross-validation details (10-fold Crossvalidation)
0.8893 ± 0.0437
Cross-validation details (10-fold Crossvalidation)
0.9526 ± 0.0055
Cross-validation details (10-fold Crossvalidation)
0.6851 ± 0.0423
Cross-validation details (10-fold Crossvalidation)
0.4835 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.3514 ± 0.0292
Cross-validation details (10-fold Crossvalidation)
0.7268 ± 0.0605
Cross-validation details (10-fold Crossvalidation)
0.8696 ± 0.0506
Cross-validation details (10-fold Crossvalidation)