Run
10453861

Run 10453861

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_components39
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_priorsnull
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_shrinkage0.1277903903170614
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_solver"lsqr"
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_store_covariancefalse
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_tol5.197047571736923e-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.

16 Evaluation measures

0.7907 ± 0.0201
Per class
Cross-validation details (10-fold Crossvalidation)
0.179 ± 0.0315
Cross-validation details (10-fold Crossvalidation)
0.1957 ± 0.013
Cross-validation details (10-fold Crossvalidation)
0.1551 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.1679 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.3754 ± 0.0253
Cross-validation details (10-fold Crossvalidation)
2126
Per class
Cross-validation details (10-fold Crossvalidation)
0.3754 ± 0.0253
Cross-validation details (10-fold Crossvalidation)
2.9134 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.9235 ± 0.0045
Cross-validation details (10-fold Crossvalidation)
0.2897 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2746 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
0.9479 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
0.1878 ± 0.0171
Cross-validation details (10-fold Crossvalidation)