Run
10457803

Run 10457803

Task 3797 (Supervised Classification) socmob Uploaded 19-05-2020 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.mu lti_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.de composition._pca.PCA,step_2=sklearn.ensemble._weight_boosting.AdaBoostClass ifier)(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.R"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_base_estimatornull
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_learning_rate1.151191019205611
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_n_estimators112
sklearn.ensemble._weight_boosting.AdaBoostClassifier(2)_random_state42
automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent(1)_columnsnull
sklearn.decomposition._pca.PCA(1)_copyfalse
sklearn.decomposition._pca.PCA(1)_iterated_power"auto"
sklearn.decomposition._pca.PCA(1)_n_components1
sklearn.decomposition._pca.PCA(1)_random_state42
sklearn.decomposition._pca.PCA(1)_svd_solver"auto"
sklearn.decomposition._pca.PCA(1)_tol0.7049643110868459
sklearn.decomposition._pca.PCA(1)_whitenfalse
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.decomposition._pca.PCA,step_2=sklearn.ensemble._weight_boosting.AdaBoostClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.decomposition._pca.PCA,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.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.decomposition._pca.PCA,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

0.9488 ± 0.0139
Per class
Cross-validation details (10-fold Crossvalidation)
0.9076 ± 0.0232
Per class
Cross-validation details (10-fold Crossvalidation)
0.7278 ± 0.069
Cross-validation details (10-fold Crossvalidation)
-0.7553 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
0.4745 ± 0.002
Cross-validation details (10-fold Crossvalidation)
0.3451 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.9092 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
1156
Per class
Cross-validation details (10-fold Crossvalidation)
0.907 ± 0.0248
Per class
Cross-validation details (10-fold Crossvalidation)
0.9092 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
0.7628 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
1.375 ± 0.0122
Cross-validation details (10-fold Crossvalidation)
0.4152 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.4752 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
1.1443 ± 0.01
Cross-validation details (10-fold Crossvalidation)
0.8522 ± 0.0343
Cross-validation details (10-fold Crossvalidation)