Run
9322

Run 9322

Task 801 (Learning Curve) diabetes Uploaded 25-11-2022 by Continuous Integration
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Flow

TEST11127b623csklearn.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 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 to None.
TEST11127b623csklearn.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"}}]
TEST11127b623csklearn.preprocessing.data.StandardScaler(1)_copytrue
TEST11127b623csklearn.preprocessing.data.StandardScaler(1)_with_meanfalse
TEST11127b623csklearn.preprocessing.data.StandardScaler(1)_with_stdtrue
TEST11127b623csklearn.dummy.DummyClassifier(1)_constantnull
TEST11127b623csklearn.dummy.DummyClassifier(1)_random_state62501
TEST11127b623csklearn.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

0.4952
Per class
0.0002 ± 0.0006
0.4544 ± 0.0014
0.4545 ± 0.0015
0.651 ± 0.0051
768
Per class
0.651 ± 0.0051
0.9331 ± 0.0046
0.9998 ± 0.0004
0.4766 ± 0.0016
0.4766 ± 0.0016
1 ± 0
0.5