Run
10560220

Run 10560220

Task 146822 (Supervised Classification) segment Uploaded 13-08-2021 by Sergey Redyuk
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, pca=sklearn.decomposition.pca.PCA,gradientboostingclassifier=sklearn.ensemb le.gradient_boosting.GradientBoostingClassifier)(2)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 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 to None.
sklearn.decomposition.pca.PCA(11)_copytrue
sklearn.decomposition.pca.PCA(11)_iterated_power"auto"
sklearn.decomposition.pca.PCA(11)_n_componentsnull
sklearn.decomposition.pca.PCA(11)_random_state41817
sklearn.decomposition.pca.PCA(11)_svd_solver"auto"
sklearn.decomposition.pca.PCA(11)_tol0.0
sklearn.decomposition.pca.PCA(11)_whitenfalse
sklearn.preprocessing.imputation.Imputer(52)_axis0
sklearn.preprocessing.imputation.Imputer(52)_copytrue
sklearn.preprocessing.imputation.Imputer(52)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(52)_strategy"median"
sklearn.preprocessing.imputation.Imputer(52)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_criterion"friedman_mse"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_initnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_learning_rate0.05
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_loss"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_max_depth6
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_max_featuresnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_max_leaf_nodesnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_min_impurity_split1e-07
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_min_samples_leaf1
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_min_samples_split2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_min_weight_fraction_leaf0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_n_estimators50
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_presort"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_random_state28544
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_subsample0.5
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(26)_warm_startfalse
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,pca=sklearn.decomposition.pca.PCA,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "pca", "step_name": "pca"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]

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

0.9939 ± 0.0028
Per class
Cross-validation details (10-fold Crossvalidation)
0.9285 ± 0.0142
Per class
Cross-validation details (10-fold Crossvalidation)
0.9167 ± 0.0167
Cross-validation details (10-fold Crossvalidation)
0.8957 ± 0.0158
Cross-validation details (10-fold Crossvalidation)
0.0382 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
0.2449
Cross-validation details (10-fold Crossvalidation)
0.9286 ± 0.0143
Cross-validation details (10-fold Crossvalidation)
2310
Per class
Cross-validation details (10-fold Crossvalidation)
0.9292 ± 0.015
Per class
Cross-validation details (10-fold Crossvalidation)
0.9286 ± 0.0143
Cross-validation details (10-fold Crossvalidation)
2.8074
Cross-validation details (10-fold Crossvalidation)
0.1561 ± 0.0176
Cross-validation details (10-fold Crossvalidation)
0.3499
Cross-validation details (10-fold Crossvalidation)
0.1245 ± 0.0131
Cross-validation details (10-fold Crossvalidation)
0.3558 ± 0.0375
Cross-validation details (10-fold Crossvalidation)
0.9286 ± 0.0143
Cross-validation details (10-fold Crossvalidation)