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1079

Run 1079

Task 733 (Supervised Regression) quake Uploaded 03-07-2024 by Continuous Integration
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Flow

TESTcc23223845sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.Simple Imputer,regressor=sklearn.linear_model._base.LinearRegression)(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``.
TESTcc23223845sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_memorynull
TESTcc23223845sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "regressor", "step_name": "regressor"}}]
TESTcc23223845sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_verbosefalse
TESTcc23223845sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TESTcc23223845sklearn.impute._base.SimpleImputer(1)_copytrue
TESTcc23223845sklearn.impute._base.SimpleImputer(1)_fill_valuenull
TESTcc23223845sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TESTcc23223845sklearn.impute._base.SimpleImputer(1)_strategy"mean"
TESTcc23223845sklearn.impute._base.SimpleImputer(1)_verbose0
TESTcc23223845sklearn.linear_model._base.LinearRegression(1)_copy_Xtrue
TESTcc23223845sklearn.linear_model._base.LinearRegression(1)_fit_intercepttrue
TESTcc23223845sklearn.linear_model._base.LinearRegression(1)_n_jobsnull
TESTcc23223845sklearn.linear_model._base.LinearRegression(1)_normalizefalse

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.

7 Evaluation measures

0.1486 ± 0.0063
0.1491 ± 0.0067
2178
0.9962 ± 0.0102
0.1894 ± 0.0107
0.189 ± 0.0103
0.9981 ± 0.0047