Run
10453497

Run 10453497

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.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_components301
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)_tol0.0031119671310082665

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

0.9912 ± 0.0121
Per class
Cross-validation details (10-fold Crossvalidation)
0.9555 ± 0.0352
Per class
Cross-validation details (10-fold Crossvalidation)
0.9041 ± 0.0757
Cross-validation details (10-fold Crossvalidation)
0.889 ± 0.0637
Cross-validation details (10-fold Crossvalidation)
0.0532 ± 0.0276
Cross-validation details (10-fold Crossvalidation)
0.4676 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.9561 ± 0.0343
Cross-validation details (10-fold Crossvalidation)
569
Per class
Cross-validation details (10-fold Crossvalidation)
0.9579 ± 0.032
Per class
Cross-validation details (10-fold Crossvalidation)
0.9561 ± 0.0343
Cross-validation details (10-fold Crossvalidation)
0.9526 ± 0.0055
Cross-validation details (10-fold Crossvalidation)
0.1138 ± 0.0586
Cross-validation details (10-fold Crossvalidation)
0.4835 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.1833 ± 0.0825
Cross-validation details (10-fold Crossvalidation)
0.3791 ± 0.17
Cross-validation details (10-fold Crossvalidation)
0.943 ± 0.0435
Cross-validation details (10-fold Crossvalidation)