Run
5

Run 5

Task 119 (Supervised Classification) diabetes Uploaded 11-01-2021 by Continuous Integration
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  • openml-python Sklearn_0.23.1. study_5 study_8 study_10 study_12 study_13 study_39 study_655 study_754 study_1257 study_1261
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Flow

TEST260ce2e22esklearn.pipeline.Pipeline(imputer=sklearn.impute._base.Simple Imputer,classifier=sklearn.dummy.DummyClassifier)(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``.
TEST260ce2e22esklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_memorynull
TEST260ce2e22esklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]
TEST260ce2e22esklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_verbosefalse
TEST260ce2e22esklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TEST260ce2e22esklearn.impute._base.SimpleImputer(1)_copytrue
TEST260ce2e22esklearn.impute._base.SimpleImputer(1)_fill_valuenull
TEST260ce2e22esklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TEST260ce2e22esklearn.impute._base.SimpleImputer(1)_strategy"mean"
TEST260ce2e22esklearn.impute._base.SimpleImputer(1)_verbose0
TEST260ce2e22esklearn.dummy.DummyClassifier(1)_constantnull
TEST260ce2e22esklearn.dummy.DummyClassifier(1)_random_state63483
TEST260ce2e22esklearn.dummy.DummyClassifier(1)_strategy"warn"

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

0.5388
Per class
Cross-validation details (10% Holdout set)
0.5659
Per class
Cross-validation details (10% Holdout set)
0.0757
Cross-validation details (10% Holdout set)
0.0091
Cross-validation details (10% Holdout set)
0.4387
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.5613
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.5725
Per class
Cross-validation details (10% Holdout set)
0.5613
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.956
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.6624
Cross-validation details (10% Holdout set)
1.3763
Cross-validation details (10% Holdout set)
0.5388
Cross-validation details (10% Holdout set)