Run
161

Run 161

Task 119 (Supervised Classification) diabetes Uploaded 29-10-2019 by Continuous Integration
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Flow

TEST2bf3a12a0dsklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.S tandardScaler,dummy=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``.
TEST2bf3a12a0dsklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,dummy=sklearn.dummy.DummyClassifier)(1)_memorynull
TEST2bf3a12a0dsklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,dummy=sklearn.dummy.DummyClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "scaler", "step_name": "scaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "dummy", "step_name": "dummy"}}]
TEST2bf3a12a0dsklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,dummy=sklearn.dummy.DummyClassifier)(1)_verbosefalse
TEST2bf3a12a0dsklearn.preprocessing.data.StandardScaler(1)_copytrue
TEST2bf3a12a0dsklearn.preprocessing.data.StandardScaler(1)_with_meanfalse
TEST2bf3a12a0dsklearn.preprocessing.data.StandardScaler(1)_with_stdtrue
TEST2bf3a12a0dsklearn.dummy.DummyClassifier(1)_constantnull
TEST2bf3a12a0dsklearn.dummy.DummyClassifier(1)_random_state62501
TEST2bf3a12a0dsklearn.dummy.DummyClassifier(1)_strategy"prior"

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% Holdout set)
0.0048
Cross-validation details (10% Holdout set)
0.4568
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.6364
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.6364
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.9955
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.4815
Cross-validation details (10% Holdout set)
1.0006
Cross-validation details (10% Holdout set)
0.5
Cross-validation details (10% Holdout set)