Run
10453871

Run 10453871

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.discriminant_analysis.LinearDiscri minantAnalysis)(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.discriminant_analysis.LinearDiscriminantAnalysis)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.discriminant_analysis.LinearDiscriminantAnalysis)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.discriminant_analysis.LinearDiscriminantAnalysis)(1)_verbosefalse
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_n_components395
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_priorsnull
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_shrinkagenull
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_solver"svd"
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_store_covariancefalse
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_tol3.949862112396927e-07

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

0.9627 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
0.754 ± 0.0204
Per class
Cross-validation details (10-fold Crossvalidation)
0.7046 ± 0.0246
Cross-validation details (10-fold Crossvalidation)
0.7152 ± 0.0203
Cross-validation details (10-fold Crossvalidation)
0.0642 ± 0.0038
Cross-validation details (10-fold Crossvalidation)
0.1679 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.7521 ± 0.0208
Cross-validation details (10-fold Crossvalidation)
2126
Per class
Cross-validation details (10-fold Crossvalidation)
0.7657 ± 0.0185
Per class
Cross-validation details (10-fold Crossvalidation)
0.7521 ± 0.0208
Cross-validation details (10-fold Crossvalidation)
2.9134 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.382 ± 0.0226
Cross-validation details (10-fold Crossvalidation)
0.2897 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.1918 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
0.6621 ± 0.0294
Cross-validation details (10-fold Crossvalidation)
0.7061 ± 0.0366
Cross-validation details (10-fold Crossvalidation)