Run
10560645

Run 10560645

Task 9978 (Supervised Classification) ozone-level-8hr Uploaded 21-08-2021 by Sergey Redyuk
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Flow

sklearn.pipeline.Pipeline(imputation=sklearn.preprocessing.imputation.Imput er,estimator=sklearn.tree.tree.DecisionTreeClassifier)(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.tree.tree.DecisionTreeClassifier(68)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(68)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(68)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(68)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(68)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(68)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(68)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(68)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(68)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(68)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(68)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(68)_random_state62186
sklearn.tree.tree.DecisionTreeClassifier(68)_splitter"best"
sklearn.pipeline.Pipeline(imputation=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(imputation=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(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

0.5828 ± 0.051
Per class
Cross-validation details (10-fold Crossvalidation)
0.8979 ± 0.0126
Per class
Cross-validation details (10-fold Crossvalidation)
0.1578 ± 0.0992
Cross-validation details (10-fold Crossvalidation)
-0.2533 ± 0.18
Cross-validation details (10-fold Crossvalidation)
0.1046 ± 0.015
Cross-validation details (10-fold Crossvalidation)
0.1186 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8954 ± 0.015
Cross-validation details (10-fold Crossvalidation)
2534
Per class
Cross-validation details (10-fold Crossvalidation)
0.9004 ± 0.0118
Per class
Cross-validation details (10-fold Crossvalidation)
0.8954 ± 0.015
Cross-validation details (10-fold Crossvalidation)
0.3398 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
0.8817 ± 0.1266
Cross-validation details (10-fold Crossvalidation)
0.2432 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.3234 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
1.3296 ± 0.0938
Cross-validation details (10-fold Crossvalidation)
0.5828 ± 0.051
Cross-validation details (10-fold Crossvalidation)