Run
10459135

Run 10459135

Task 9981 (Supervised Classification) cnae-9 Uploaded 20-05-2020 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.decomposition._fastica.FastICA,ste p_1=sklearn.svm._classes.SVC)(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.svm._classes.SVC(4)_C1409.3317427539928
sklearn.svm._classes.SVC(4)_break_tiesfalse
sklearn.svm._classes.SVC(4)_cache_size200
sklearn.svm._classes.SVC(4)_class_weightnull
sklearn.svm._classes.SVC(4)_coef022.336094104025804
sklearn.svm._classes.SVC(4)_decision_function_shape"ovo"
sklearn.svm._classes.SVC(4)_degree5
sklearn.svm._classes.SVC(4)_gamma0.015621195737891542
sklearn.svm._classes.SVC(4)_kernel"poly"
sklearn.svm._classes.SVC(4)_max_iter-1
sklearn.svm._classes.SVC(4)_probabilityfalse
sklearn.svm._classes.SVC(4)_random_state42
sklearn.svm._classes.SVC(4)_shrinkingfalse
sklearn.svm._classes.SVC(4)_tol0.0002759997170535941
sklearn.svm._classes.SVC(4)_verbosefalse
sklearn.decomposition._fastica.FastICA(1)_algorithm"parallel"
sklearn.decomposition._fastica.FastICA(1)_fun"cube"
sklearn.decomposition._fastica.FastICA(1)_fun_argsnull
sklearn.decomposition._fastica.FastICA(1)_max_iter196
sklearn.decomposition._fastica.FastICA(1)_n_components701
sklearn.decomposition._fastica.FastICA(1)_random_state42
sklearn.decomposition._fastica.FastICA(1)_tol0.4661113316817489
sklearn.decomposition._fastica.FastICA(1)_w_initnull
sklearn.decomposition._fastica.FastICA(1)_whitenfalse
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._fastica.FastICA,step_1=sklearn.svm._classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._fastica.FastICA,step_1=sklearn.svm._classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._fastica.FastICA,step_1=sklearn.svm._classes.SVC)(1)_verbosefalse

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

0.95 ± 0.0174
Per class
Cross-validation details (10-fold Crossvalidation)
0.9113 ± 0.031
Per class
Cross-validation details (10-fold Crossvalidation)
0.9 ± 0.0348
Cross-validation details (10-fold Crossvalidation)
0.9063 ± 0.0326
Cross-validation details (10-fold Crossvalidation)
0.0198 ± 0.0069
Cross-validation details (10-fold Crossvalidation)
0.1975
Cross-validation details (10-fold Crossvalidation)
0.9111 ± 0.0309
Cross-validation details (10-fold Crossvalidation)
1080
Per class
Cross-validation details (10-fold Crossvalidation)
0.9149 ± 0.028
Per class
Cross-validation details (10-fold Crossvalidation)
0.9111 ± 0.0309
Cross-validation details (10-fold Crossvalidation)
3.1699
Cross-validation details (10-fold Crossvalidation)
0.1 ± 0.0348
Cross-validation details (10-fold Crossvalidation)
0.3143
Cross-validation details (10-fold Crossvalidation)
0.1405 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
0.4472 ± 0.0735
Cross-validation details (10-fold Crossvalidation)
0.9111 ± 0.0309
Cross-validation details (10-fold Crossvalidation)