Run
10560633

Run 10560633

Task 9981 (Supervised Classification) cnae-9 Uploaded 21-08-2021 by Sergey Redyuk
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(imputation=sklearn.preprocessing.imputation.Imput er,estimator=sklearn.naive_bayes.GaussianNB)(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 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 to None.
sklearn.preprocessing.imputation.Imputer(54)_axis0
sklearn.preprocessing.imputation.Imputer(54)_copytrue
sklearn.preprocessing.imputation.Imputer(54)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(54)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(54)_verbose0
sklearn.naive_bayes.GaussianNB(21)_priorsnull
sklearn.pipeline.Pipeline(imputation=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.naive_bayes.GaussianNB)(2)_memorynull
sklearn.pipeline.Pipeline(imputation=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.naive_bayes.GaussianNB)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputation", "step_name": "imputation"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]

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

0.9686 ± 0.0143
Per class
Cross-validation details (10-fold Crossvalidation)
0.8831 ± 0.0462
Per class
Cross-validation details (10-fold Crossvalidation)
0.8708 ± 0.0482
Cross-validation details (10-fold Crossvalidation)
0.8793 ± 0.0448
Cross-validation details (10-fold Crossvalidation)
0.0255 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
0.1975
Cross-validation details (10-fold Crossvalidation)
0.8852 ± 0.0428
Cross-validation details (10-fold Crossvalidation)
1080
Per class
Cross-validation details (10-fold Crossvalidation)
0.8889 ± 0.041
Per class
Cross-validation details (10-fold Crossvalidation)
0.8852 ± 0.0428
Cross-validation details (10-fold Crossvalidation)
3.1699
Cross-validation details (10-fold Crossvalidation)
0.129 ± 0.0479
Cross-validation details (10-fold Crossvalidation)
0.3143
Cross-validation details (10-fold Crossvalidation)
0.1595 ± 0.0308
Cross-validation details (10-fold Crossvalidation)
0.5076 ± 0.0979
Cross-validation details (10-fold Crossvalidation)
0.8852 ± 0.0428
Cross-validation details (10-fold Crossvalidation)