Run
9244

Run 9244

Task 119 (Supervised Classification) diabetes Uploaded 25-11-2022 by Continuous Integration
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Flow

TESTbbaf9bd6d2sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data. StandardScaler,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``.
TESTbbaf9bd6d2sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=sklearn.dummy.DummyClassifier)(1)_memorynull
TESTbbaf9bd6d2sklearn.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"}}]
TESTbbaf9bd6d2sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=sklearn.dummy.DummyClassifier)(1)_verbosefalse
TESTbbaf9bd6d2sklearn.preprocessing._data.StandardScaler(1)_copytrue
TESTbbaf9bd6d2sklearn.preprocessing._data.StandardScaler(1)_with_meanfalse
TESTbbaf9bd6d2sklearn.preprocessing._data.StandardScaler(1)_with_stdtrue
TESTbbaf9bd6d2sklearn.dummy.DummyClassifier(1)_constantnull
TESTbbaf9bd6d2sklearn.dummy.DummyClassifier(1)_random_state62501
TESTbbaf9bd6d2sklearn.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