Run
10559806

Run 10559806

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 10-03-2021 by Fabrice Normandin
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Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,svc=sklearn.svm.classes.SVC)(7)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(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(7)_memorynull
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(7)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(7)_verbosefalse
sklearn.preprocessing.data.StandardScaler(41)_copytrue
sklearn.preprocessing.data.StandardScaler(41)_with_meantrue
sklearn.preprocessing.data.StandardScaler(41)_with_stdtrue
sklearn.svm.classes.SVC(43)_C417.82975185689014
sklearn.svm.classes.SVC(43)_cache_size200
sklearn.svm.classes.SVC(43)_class_weightnull
sklearn.svm.classes.SVC(43)_coef00.0
sklearn.svm.classes.SVC(43)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(43)_degree3
sklearn.svm.classes.SVC(43)_gamma335.71567145206404
sklearn.svm.classes.SVC(43)_kernel"linear"
sklearn.svm.classes.SVC(43)_max_iter-1
sklearn.svm.classes.SVC(43)_probabilityfalse
sklearn.svm.classes.SVC(43)_random_state61577
sklearn.svm.classes.SVC(43)_shrinkingtrue
sklearn.svm.classes.SVC(43)_tol0.001
sklearn.svm.classes.SVC(43)_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

0.4982 ± 0.0037
Per class
Cross-validation details (10-fold Crossvalidation)
0.6578
Per class
Cross-validation details (10-fold Crossvalidation)
-0.0053 ± 0.0109
Cross-validation details (10-fold Crossvalidation)
0.2521 ± 0.0202
Cross-validation details (10-fold Crossvalidation)
0.2406 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.7594 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
748
Per class
Cross-validation details (10-fold Crossvalidation)
0.5802
Per class
Cross-validation details (10-fold Crossvalidation)
0.7594 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
0.6628 ± 0.019
Cross-validation details (10-fold Crossvalidation)
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.4906 ± 0.008
Cross-validation details (10-fold Crossvalidation)
1.152 ± 0.0145
Cross-validation details (10-fold Crossvalidation)
0.4982 ± 0.0037
Cross-validation details (10-fold Crossvalidation)