Run
4105

Run 4105

Task 115 (Supervised Classification) diabetes Uploaded 05-11-2019 by Continuous Integration
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Varian ceThreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold, 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.tree.tree.DecisionTreeClassifier(4)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(4)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(4)_max_depth4
sklearn.tree.tree.DecisionTreeClassifier(4)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(4)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(4)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(4)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(4)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(4)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(4)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(4)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(4)_random_state62501
sklearn.tree.tree.DecisionTreeClassifier(4)_splitter"best"
sklearn.impute._base.SimpleImputer(2)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(2)_copytrue
sklearn.impute._base.SimpleImputer(2)_fill_valuenull
sklearn.impute._base.SimpleImputer(2)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(2)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(2)_verbose0
sklearn.feature_selection.variance_threshold.VarianceThreshold(5)_threshold0.1
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,Estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,Estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"step_name": "Imputer", "key": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"step_name": "VarianceThreshold", "key": "VarianceThreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"step_name": "Estimator", "key": "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

0.796 ± 0.041
Per class
Cross-validation details (10-fold Crossvalidation)
0.7324 ± 0.0452
Per class
Cross-validation details (10-fold Crossvalidation)
0.4127 ± 0.0932
Cross-validation details (10-fold Crossvalidation)
0.3145 ± 0.0647
Cross-validation details (10-fold Crossvalidation)
0.3105 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
0.4545 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.7318 ± 0.0408
Cross-validation details (10-fold Crossvalidation)
768
Per class
Cross-validation details (10-fold Crossvalidation)
0.7332 ± 0.0353
Per class
Cross-validation details (10-fold Crossvalidation)
0.7318 ± 0.0408
Cross-validation details (10-fold Crossvalidation)
0.9331 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
0.6832 ± 0.0594
Cross-validation details (10-fold Crossvalidation)
0.4766 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.4198 ± 0.0198
Cross-validation details (10-fold Crossvalidation)
0.8807 ± 0.0422
Cross-validation details (10-fold Crossvalidation)
0.7074 ± 0.0501
Cross-validation details (10-fold Crossvalidation)