Run
10455083

Run 10455083

Task 9914 (Supervised Classification) wilt Uploaded 19-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
Issue #Downvotes for this reason By


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_components176
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_priorsnull
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_shrinkage0.9932340840515207
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_solver"lsqr"
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_store_covariancefalse
sklearn.discriminant_analysis.LinearDiscriminantAnalysis(4)_tol1.8212326778593128e-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

0.678 ± 0.0404
Per class
Cross-validation details (10-fold Crossvalidation)
0.9013 ± 0.0087
Per class
Cross-validation details (10-fold Crossvalidation)
0.0444 ± 0.078
Cross-validation details (10-fold Crossvalidation)
-1.8395 ± 0.1554
Cross-validation details (10-fold Crossvalidation)
0.1444 ± 0.0082
Cross-validation details (10-fold Crossvalidation)
0.1022 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.9002 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
4839
Per class
Cross-validation details (10-fold Crossvalidation)
0.9025 ± 0.0076
Per class
Cross-validation details (10-fold Crossvalidation)
0.9002 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
0.3029 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
1.4127 ± 0.0825
Cross-validation details (10-fold Crossvalidation)
0.2259 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
0.276 ± 0.0134
Cross-validation details (10-fold Crossvalidation)
1.2216 ± 0.0605
Cross-validation details (10-fold Crossvalidation)
0.5227 ± 0.039
Cross-validation details (10-fold Crossvalidation)