Run
10560680

Run 10560680

Task 167119 (Supervised Classification) jungle_chess_2pcs_raw_endgame_complete Uploaded 21-08-2021 by Sergey Redyuk
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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

0.8326 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
0.6819 ± 0.007
Per class
Cross-validation details (10-fold Crossvalidation)
0.4485 ± 0.0127
Cross-validation details (10-fold Crossvalidation)
0.3245 ± 0.0066
Cross-validation details (10-fold Crossvalidation)
0.282 ± 0.002
Cross-validation details (10-fold Crossvalidation)
0.3832 ± 0
Cross-validation details (10-fold Crossvalidation)
0.6935 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
44819
Per class
Cross-validation details (10-fold Crossvalidation)
0.6761 ± 0.0072
Per class
Cross-validation details (10-fold Crossvalidation)
0.6935 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
1.3491 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.7361 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.4377 ± 0
Cross-validation details (10-fold Crossvalidation)
0.3687 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
0.8423 ± 0.0059
Cross-validation details (10-fold Crossvalidation)
0.5498 ± 0.0069
Cross-validation details (10-fold Crossvalidation)