Run
10453517

Run 10453517

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_components287
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_priorsnull
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_shrinkage0.43245919028902535
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_solver"eigen"
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_store_covariancefalse
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_tol0.020418156426603152

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

0.9648 ± 0.0249
Per class
Cross-validation details (10-fold Crossvalidation)
0.8748 ± 0.059
Per class
Cross-validation details (10-fold Crossvalidation)
0.7277 ± 0.126
Cross-validation details (10-fold Crossvalidation)
0.7192 ± 0.0956
Cross-validation details (10-fold Crossvalidation)
0.1314 ± 0.0417
Cross-validation details (10-fold Crossvalidation)
0.4676 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.8805 ± 0.05
Cross-validation details (10-fold Crossvalidation)
569
Per class
Cross-validation details (10-fold Crossvalidation)
0.8966 ± 0.0344
Per class
Cross-validation details (10-fold Crossvalidation)
0.8805 ± 0.05
Cross-validation details (10-fold Crossvalidation)
0.9526 ± 0.0055
Cross-validation details (10-fold Crossvalidation)
0.281 ± 0.089
Cross-validation details (10-fold Crossvalidation)
0.4835 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.3015 ± 0.0619
Cross-validation details (10-fold Crossvalidation)
0.6235 ± 0.1275
Cross-validation details (10-fold Crossvalidation)
0.8415 ± 0.068
Cross-validation details (10-fold Crossvalidation)