Run
10453394

Run 10453394

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_components378
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_priorsnull
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_shrinkage0.008364168788839166
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_solver"lsqr"
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_store_covariancefalse
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_tol0.00011551405665777555

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

0.9823 ± 0.0143
Per class
Cross-validation details (10-fold Crossvalidation)
0.9151 ± 0.0397
Per class
Cross-validation details (10-fold Crossvalidation)
0.8157 ± 0.0861
Cross-validation details (10-fold Crossvalidation)
0.7486 ± 0.0713
Cross-validation details (10-fold Crossvalidation)
0.1249 ± 0.031
Cross-validation details (10-fold Crossvalidation)
0.4676 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.9174 ± 0.036
Cross-validation details (10-fold Crossvalidation)
569
Per class
Cross-validation details (10-fold Crossvalidation)
0.925 ± 0.0262
Per class
Cross-validation details (10-fold Crossvalidation)
0.9174 ± 0.036
Cross-validation details (10-fold Crossvalidation)
0.9526 ± 0.0055
Cross-validation details (10-fold Crossvalidation)
0.267 ± 0.066
Cross-validation details (10-fold Crossvalidation)
0.4835 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.2444 ± 0.0526
Cross-validation details (10-fold Crossvalidation)
0.5055 ± 0.1084
Cross-validation details (10-fold Crossvalidation)
0.8911 ± 0.0496
Cross-validation details (10-fold Crossvalidation)