OpenML
513

Run 513

Task 733 (Supervised Regression) quake Uploaded 11-01-2024 by Continuous Integration
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

TEST76ccc16365sklearn.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``.
TEST76ccc16365sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_memorynull
TEST76ccc16365sklearn.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"}}]
TEST76ccc16365sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression)(1)_verbosefalse
TEST76ccc16365sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TEST76ccc16365sklearn.impute._base.SimpleImputer(1)_copytrue
TEST76ccc16365sklearn.impute._base.SimpleImputer(1)_fill_valuenull
TEST76ccc16365sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TEST76ccc16365sklearn.impute._base.SimpleImputer(1)_strategy"mean"
TEST76ccc16365sklearn.impute._base.SimpleImputer(1)_verbose0
TEST76ccc16365sklearn.linear_model._base.LinearRegression(1)_copy_Xtrue
TEST76ccc16365sklearn.linear_model._base.LinearRegression(1)_fit_intercepttrue
TEST76ccc16365sklearn.linear_model._base.LinearRegression(1)_n_jobsnull
TEST76ccc16365sklearn.linear_model._base.LinearRegression(1)_normalizefalse
TEST76ccc16365sklearn.linear_model._base.LinearRegression(1)_positivefalse

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