Run
10459754

Run 10459754

Task 3711 (Supervised Classification) elevators Uploaded 20-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
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Flow

sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.on e_hot_encoding.OneHotEncoderComponent,step_1=sklearn.linear_model._stochast ic_gradient.SGDClassifier)(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.linear_model._stochastic_gradient.SGDClassifier(2)_alpha0.00015457197934913453
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_averagetrue
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_class_weightnull
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_early_stoppingfalse
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_epsilon17.646208993527047
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_eta00.0
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_fit_interceptfalse
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_l1_ratio0.24092456298304138
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_learning_rate"optimal"
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_loss"hinge"
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_max_iter1006
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_n_iter_no_change87
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_n_jobs1
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_penalty"l2"
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_power_t0.9403077060239737
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_random_state42
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_shuffletrue
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_tol0.30704495891258793
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_validation_fraction0.1
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_verbose0
sklearn.linear_model._stochastic_gradient.SGDClassifier(2)_warm_startfalse
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.linear_model._stochastic_gradient.SGDClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.linear_model._stochastic_gradient.SGDClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.linear_model._stochastic_gradient.SGDClassifier)(1)_verbosefalse

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.

18 Evaluation measures

0.5266 ± 0.0136
Per class
Cross-validation details (10-fold Crossvalidation)
0.6056 ± 0.0123
Per class
Cross-validation details (10-fold Crossvalidation)
0.0561 ± 0.0287
Cross-validation details (10-fold Crossvalidation)
0.0453 ± 0.034
Cross-validation details (10-fold Crossvalidation)
0.3824 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
0.4271 ± 0
Cross-validation details (10-fold Crossvalidation)
0.6176 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
16599
Per class
Cross-validation details (10-fold Crossvalidation)
0.5974 ± 0.0126
Per class
Cross-validation details (10-fold Crossvalidation)
0.6176 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
0.8921 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8953 ± 0.0319
Cross-validation details (10-fold Crossvalidation)
0.4621 ± 0
Cross-validation details (10-fold Crossvalidation)
0.6184 ± 0.011
Cross-validation details (10-fold Crossvalidation)
1.3381 ± 0.0239
Cross-validation details (10-fold Crossvalidation)
0.5266 ± 0.0136
Cross-validation details (10-fold Crossvalidation)