OpenML
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Run 3368

Task 733 (Supervised Regression) quake Uploaded 12-01-2024 by Continuous Integration
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Flow

TEST496cb42410sklearn.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``.
TEST496cb42410sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_memorynull
TEST496cb42410sklearn.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"}}]
TEST496cb42410sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_verbosefalse
TEST496cb42410sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TEST496cb42410sklearn.impute._base.SimpleImputer(1)_copytrue
TEST496cb42410sklearn.impute._base.SimpleImputer(1)_fill_valuenull
TEST496cb42410sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TEST496cb42410sklearn.impute._base.SimpleImputer(1)_strategy"mean"
TEST496cb42410sklearn.impute._base.SimpleImputer(1)_verbose0
TEST496cb42410sklearn.linear_model._base.LinearRegression(1)_copy_Xtrue
TEST496cb42410sklearn.linear_model._base.LinearRegression(1)_fit_intercepttrue
TEST496cb42410sklearn.linear_model._base.LinearRegression(1)_n_jobsnull
TEST496cb42410sklearn.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