Run
10463029

Run 10463029

Task 3021 (Supervised Classification) sick Uploaded 21-05-2020 by Marc Zöller
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • automl_meta_features openml-python Sklearn_0.22.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.on e_hot_encoding.OneHotEncoderComponent,step_1=automl.components.data_preproc essing.imputation.ImputationComponent,step_2=sklearn.ensemble._weight_boost ing.AdaBoostClassifier)(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.ensemble._weight_boosting.AdaBoostClassifier(2)_algorithm"SAMME"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_base_estimatornull
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_learning_rate0.0017757509026630096
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_n_estimators1001
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_random_state42
automl.components.data_preprocessing.imputation.ImputationComponent(1)_add_indicatorfalse
automl.components.data_preprocessing.imputation.ImputationComponent(1)_missing_valuesNaN
automl.components.data_preprocessing.imputation.ImputationComponent(1)_strategy"mean"
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=automl.components.data_preprocessing.imputation.ImputationComponent,step_2=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=automl.components.data_preprocessing.imputation.ImputationComponent,step_2=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(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"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_2", "step_name": "step_2"}}]
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=automl.components.data_preprocessing.imputation.ImputationComponent,step_2=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(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

0.9326 ± 0.0356
Per class
Cross-validation details (10-fold Crossvalidation)
0.9679 ± 0.0114
Per class
Cross-validation details (10-fold Crossvalidation)
0.742 ± 0.0839
Cross-validation details (10-fold Crossvalidation)
-5.5439 ± 0.0784
Cross-validation details (10-fold Crossvalidation)
0.2902 ± 0.0034
Cross-validation details (10-fold Crossvalidation)
0.1152 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
0.9655 ± 0.013
Cross-validation details (10-fold Crossvalidation)
3772
Per class
Cross-validation details (10-fold Crossvalidation)
0.9725 ± 0.0088
Per class
Cross-validation details (10-fold Crossvalidation)
0.9655 ± 0.013
Cross-validation details (10-fold Crossvalidation)
0.3324 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
2.5198 ± 0.0344
Cross-validation details (10-fold Crossvalidation)
0.2398 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
0.2988 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
1.2463 ± 0.0234
Cross-validation details (10-fold Crossvalidation)
0.9311 ± 0.0353
Cross-validation details (10-fold Crossvalidation)