Run
10453830

Run 10453830

Task 9979 (Supervised Classification) cardiotocography 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.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.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(1)_verbosefalse
sklearn.svm._classes.SVC(4)_C1.00265039328167e-06
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)_gamma"scale"
sklearn.svm._classes.SVC(4)_kernel"linear"
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)_tol3.0734150058750543e-06
sklearn.svm._classes.SVC(4)_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

0.5444 ± 0.0067
Per class
Cross-validation details (10-fold Crossvalidation)
0.0924 ± 0.0147
Cross-validation details (10-fold Crossvalidation)
0.1821 ± 0.011
Cross-validation details (10-fold Crossvalidation)
0.1351 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.1679 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.3246 ± 0.0114
Cross-validation details (10-fold Crossvalidation)
2126
Per class
Cross-validation details (10-fold Crossvalidation)
0.3246 ± 0.0114
Cross-validation details (10-fold Crossvalidation)
2.9134 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.8044 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
0.2897 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.3675 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
1.2686 ± 0.0107
Cross-validation details (10-fold Crossvalidation)
0.1336 ± 0.0066
Cross-validation details (10-fold Crossvalidation)