Run
10463430

Run 10463430

Task 3021 (Supervised Classification) sick Uploaded 21-05-2020 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.impute._base.MissingIndicator,step _1=sklearn.preprocessing._discretization.KBinsDiscretizer,step_2=sklearn.sv m._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)_C205.38891403572043
sklearn.svm._classes.SVC(4)_break_tiestrue
sklearn.svm._classes.SVC(4)_cache_size200
sklearn.svm._classes.SVC(4)_class_weightnull
sklearn.svm._classes.SVC(4)_coef00.0
sklearn.svm._classes.SVC(4)_decision_function_shape"ovr"
sklearn.svm._classes.SVC(4)_degree3
sklearn.svm._classes.SVC(4)_gamma105.3763298934097
sklearn.svm._classes.SVC(4)_kernel"rbf"
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)_tol4.644402321048259e-07
sklearn.svm._classes.SVC(4)_verbosefalse
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_encode"onehot-dense"
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_n_bins18
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_strategy"kmeans"
sklearn.impute._base.MissingIndicator(1)_error_on_newtrue
sklearn.impute._base.MissingIndicator(1)_features"all"
sklearn.impute._base.MissingIndicator(1)_missing_valuesNaN
sklearn.impute._base.MissingIndicator(1)_sparse"auto"
sklearn.pipeline.Pipeline(step_0=sklearn.impute._base.MissingIndicator,step_1=sklearn.preprocessing._discretization.KBinsDiscretizer,step_2=sklearn.svm._classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.impute._base.MissingIndicator,step_1=sklearn.preprocessing._discretization.KBinsDiscretizer,step_2=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"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_2", "step_name": "step_2"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.impute._base.MissingIndicator,step_1=sklearn.preprocessing._discretization.KBinsDiscretizer,step_2=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.

16 Evaluation measures

0.5
Per class
Cross-validation details (10-fold Crossvalidation)
0.2417 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
0.0612 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.1152 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
0.9388 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
3772
Per class
Cross-validation details (10-fold Crossvalidation)
0.9388 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.3324 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
0.5317 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
0.2398 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
0.2475 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
1.0321 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)