Run
10560507

Run 10560507

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 14-08-2021 by Sergey Redyuk
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Flow

sklearn.pipeline.Pipeline(nystroem=sklearn.kernel_approximation.Nystroem,fe atureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,gaussi annb=sklearn.naive_bayes.GaussianNB)(2)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 to None.
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_affinity"euclidean"
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_compute_full_tree"auto"
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_connectivitynull
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_linkage"average"
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_memorynull
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_n_clusters2
sklearn.cluster.hierarchical.FeatureAgglomeration(5)_pooling_func{"oml-python:serialized_object": "function", "value": "numpy.mean"}
sklearn.pipeline.Pipeline(nystroem=sklearn.kernel_approximation.Nystroem,featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,gaussiannb=sklearn.naive_bayes.GaussianNB)(2)_memorynull
sklearn.pipeline.Pipeline(nystroem=sklearn.kernel_approximation.Nystroem,featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,gaussiannb=sklearn.naive_bayes.GaussianNB)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "nystroem", "step_name": "nystroem"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "featureagglomeration", "step_name": "featureagglomeration"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gaussiannb", "step_name": "gaussiannb"}}]
sklearn.kernel_approximation.Nystroem(4)_coef0null
sklearn.kernel_approximation.Nystroem(4)_degreenull
sklearn.kernel_approximation.Nystroem(4)_gamma0.15000000000000002
sklearn.kernel_approximation.Nystroem(4)_kernel"laplacian"
sklearn.kernel_approximation.Nystroem(4)_kernel_paramsnull
sklearn.kernel_approximation.Nystroem(4)_n_components9
sklearn.kernel_approximation.Nystroem(4)_random_state54379
sklearn.naive_bayes.GaussianNB(21)_priorsnull

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

0.5565 ± 0.0813
Per class
Cross-validation details (10-fold Crossvalidation)
0.6416 ± 0.1741
Per class
Cross-validation details (10-fold Crossvalidation)
0.0638 ± 0.1127
Cross-validation details (10-fold Crossvalidation)
-0.3664 ± 0.3085
Cross-validation details (10-fold Crossvalidation)
0.428 ± 0.0721
Cross-validation details (10-fold Crossvalidation)
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.627 ± 0.1814
Cross-validation details (10-fold Crossvalidation)
748
Per class
Cross-validation details (10-fold Crossvalidation)
0.6612 ± 0.0915
Per class
Cross-validation details (10-fold Crossvalidation)
0.627 ± 0.1814
Cross-validation details (10-fold Crossvalidation)
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
1.1789 ± 0.1947
Cross-validation details (10-fold Crossvalidation)
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.4975 ± 0.0573
Cross-validation details (10-fold Crossvalidation)
1.1683 ± 0.1316
Cross-validation details (10-fold Crossvalidation)
0.535 ± 0.0506
Cross-validation details (10-fold Crossvalidation)