Run
10452588

Run 10452588

Task 1 (Supervised Classification) anneal Uploaded 27-04-2020 by Arlind Kadra
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • openml-python Sklearn_0.22.2.post1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.tree._classes.DecisionTreeClassifier)(3)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.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier)(3)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier)(3)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier)(3)_verbosefalse
sklearn.impute._base.SimpleImputer(14)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(14)_copytrue
sklearn.impute._base.SimpleImputer(14)_fill_valuenull
sklearn.impute._base.SimpleImputer(14)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(14)_strategy"mean"
sklearn.impute._base.SimpleImputer(14)_verbose0
sklearn.tree._classes.DecisionTreeClassifier(4)_ccp_alpha0.0
sklearn.tree._classes.DecisionTreeClassifier(4)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(4)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(4)_max_depth5
sklearn.tree._classes.DecisionTreeClassifier(4)_max_featuresnull
sklearn.tree._classes.DecisionTreeClassifier(4)_max_leaf_nodesnull
sklearn.tree._classes.DecisionTreeClassifier(4)_min_impurity_decrease0.0
sklearn.tree._classes.DecisionTreeClassifier(4)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(4)_min_samples_leaf1
sklearn.tree._classes.DecisionTreeClassifier(4)_min_samples_split2
sklearn.tree._classes.DecisionTreeClassifier(4)_min_weight_fraction_leaf0.0
sklearn.tree._classes.DecisionTreeClassifier(4)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(4)_random_state51362
sklearn.tree._classes.DecisionTreeClassifier(4)_splitter"best"

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.

17 Evaluation measures

0.9866 ± 0.0159
Per class
Cross-validation details (10-fold Crossvalidation)
0.9779 ± 0.012
Per class
Cross-validation details (10-fold Crossvalidation)
0.9477 ± 0.0241
Cross-validation details (10-fold Crossvalidation)
0.9328 ± 0.0361
Cross-validation details (10-fold Crossvalidation)
0.0099 ± 0.0045
Cross-validation details (10-fold Crossvalidation)
0.1343 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.9788 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
898
Per class
Cross-validation details (10-fold Crossvalidation)
0.9804 ± 0.0107
Per class
Cross-validation details (10-fold Crossvalidation)
0.9788 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
1.1915 ± 0.0248
Cross-validation details (10-fold Crossvalidation)
0.0738 ± 0.0337
Cross-validation details (10-fold Crossvalidation)
0.2582 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
0.0795 ± 0.0254
Cross-validation details (10-fold Crossvalidation)
0.3078 ± 0.0985
Cross-validation details (10-fold Crossvalidation)