Run
10587789

Run 10587789

Task 359945 (Supervised Regression) us_crime Uploaded 01-06-2022 by Sergey Redyuk
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Flow

sklearn.pipeline.Pipeline(easypreprocessor=dabl.preprocessing.EasyPreproces sor,simpleregressor=dabl.models.SimpleRegressor)(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``.
sklearn.pipeline.Pipeline(easypreprocessor=dabl.preprocessing.EasyPreprocessor,simpleregressor=dabl.models.SimpleRegressor)(1)_memorynull
sklearn.pipeline.Pipeline(easypreprocessor=dabl.preprocessing.EasyPreprocessor,simpleregressor=dabl.models.SimpleRegressor)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "easypreprocessor", "step_name": "easypreprocessor"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "simpleregressor", "step_name": "simpleregressor"}}]
sklearn.pipeline.Pipeline(easypreprocessor=dabl.preprocessing.EasyPreprocessor,simpleregressor=dabl.models.SimpleRegressor)(1)_verbosefalse
dabl.preprocessing.EasyPreprocessor(1)_force_imputationtrue
dabl.preprocessing.EasyPreprocessor(1)_scaletrue
dabl.preprocessing.EasyPreprocessor(1)_typesnull
dabl.preprocessing.EasyPreprocessor(1)_verbose0
dabl.models.SimpleRegressor(1)_random_state42
dabl.models.SimpleRegressor(1)_refittrue
dabl.models.SimpleRegressor(1)_shuffletrue
dabl.models.SimpleRegressor(1)_type_hintsnull
dabl.models.SimpleRegressor(1)_verbose0

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

0.1783 ± 0.0135
Cross-validation details (10-fold Crossvalidation)
1994
Cross-validation details (10-fold Crossvalidation)
0.2329 ± 0.0205
Cross-validation details (10-fold Crossvalidation)