Run
10417392

Run 10417392

Task 2295 (Supervised Regression) cholesterol Uploaded 14-11-2019 by Christian Geißler
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"mean"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)_verbosefalse
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_alpha1.8346779344534167e-06
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_averagefalse
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_early_stoppingtrue
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_epsilon0.1
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_eta00.0010265440490937324
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_fit_intercepttrue
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_l1_ratio0.06466476799534387
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_learning_rate"invscaling"
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_loss"squared_loss"
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_max_iter7386.074563255982
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_n_iter_no_change5
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_penalty"l2"
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_power_t0.22744864568193984
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_random_state59044
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_shuffletrue
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_tol1.6166849965715605e-05
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_validation_fraction0.1
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_verbose0
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_warm_startfalse

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

Mean absolute error
3508615170729.6 ± 1230400829573.2
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
39.3139 ± 6.092
Cross-validation details (10-fold Crossvalidation)
Number of instances
303
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
89246269347.447 ± 36352832855.41
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
51.6914 ± 10.5853
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
3775038614525.8 ± 1214692408077.8
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
73030294049.423 ± 28622629147.43
Cross-validation details (10-fold Crossvalidation)