Run
4

Run 4

Task 119 (Supervised Classification) diabetes Uploaded 29-10-2019 by Continuous Integration
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  • openml-python Sklearn_0.21.2. study_6 study_17 study_3170 study_3608 study_3994 study_3996 study_3999 study_4418 study_5311 study_8310 study_8624 study_8625 study_8626 study_9361 study_9363 study_9365 study_11766 study_11768 study_11770 study_11772 study_11774 study_11997 study_12006 study_13178 study_17156 study_17158
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Flow

TEST7cd14d8178sklearn.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``.
TEST7cd14d8178sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_memorynull
TEST7cd14d8178sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_steps[{"value": {"step_name": "imputer", "key": "imputer"}, "oml-python:serialized_object": "component_reference"}, {"value": {"step_name": "classifier", "key": "classifier"}, "oml-python:serialized_object": "component_reference"}]
TEST7cd14d8178sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_verbosefalse
TEST7cd14d8178sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TEST7cd14d8178sklearn.impute._base.SimpleImputer(1)_copytrue
TEST7cd14d8178sklearn.impute._base.SimpleImputer(1)_fill_valuenull
TEST7cd14d8178sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TEST7cd14d8178sklearn.impute._base.SimpleImputer(1)_strategy"mean"
TEST7cd14d8178sklearn.impute._base.SimpleImputer(1)_verbose0
TEST7cd14d8178sklearn.dummy.DummyClassifier(1)_constantnull
TEST7cd14d8178sklearn.dummy.DummyClassifier(1)_random_state62250
TEST7cd14d8178sklearn.dummy.DummyClassifier(1)_strategy"stratified"

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

0.5163
Per class
Cross-validation details (10% Holdout set)
0.5579
Per class
Cross-validation details (10% Holdout set)
0.0335
Cross-validation details (10% Holdout set)
0.018
Cross-validation details (10% Holdout set)
0.4348
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.5652
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.5529
Per class
Cross-validation details (10% Holdout set)
0.5652
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.9474
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.6594
Cross-validation details (10% Holdout set)
1.3701
Cross-validation details (10% Holdout set)
0.5163
Cross-validation details (10% Holdout set)