Run
10453899

Run 10453899

Task 9979 (Supervised Classification) cardiotocography 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.R"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_base_estimatornull
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_learning_rate1.2164814423125434
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_n_estimators272
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.

16 Evaluation measures

0.7655 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
0.346 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
0.3083 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
0.1266 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.1679 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.4779 ± 0.0029
Cross-validation details (10-fold Crossvalidation)
2126
Per class
Cross-validation details (10-fold Crossvalidation)
0.4779 ± 0.0029
Cross-validation details (10-fold Crossvalidation)
2.9134 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.7539 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
0.2897 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2482 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.8566 ± 0.0022
Cross-validation details (10-fold Crossvalidation)
0.3
Cross-validation details (10-fold Crossvalidation)