Run
10464908

Run 10464908

Task 13 (Supervised Classification) breast-cancer Uploaded 18-07-2020 by Qibin Liang
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.tree._classes.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 it to 'passthrough' or ``None``.
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier)(2)_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)(2)_verbosefalse
sklearn.impute._base.SimpleImputer(13)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(13)_copytrue
sklearn.impute._base.SimpleImputer(13)_fill_valuenull
sklearn.impute._base.SimpleImputer(13)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(13)_strategy"mean"
sklearn.impute._base.SimpleImputer(13)_verbose0
sklearn.tree._classes.DecisionTreeClassifier(3)_ccp_alpha0.0
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth3
sklearn.tree._classes.DecisionTreeClassifier(3)_max_featuresnull
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodesnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.0
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.12
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.25
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.0
sklearn.tree._classes.DecisionTreeClassifier(3)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state6169
sklearn.tree._classes.DecisionTreeClassifier(3)_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.

18 Evaluation measures

0.6624 ± 0.085
Per class
Cross-validation details (10-fold Crossvalidation)
0.7132 ± 0.0827
Per class
Cross-validation details (10-fold Crossvalidation)
0.2833 ± 0.1991
Cross-validation details (10-fold Crossvalidation)
0.134 ± 0.0903
Cross-validation details (10-fold Crossvalidation)
0.3561 ± 0.0283
Cross-validation details (10-fold Crossvalidation)
0.4183 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
0.7413 ± 0.0807
Cross-validation details (10-fold Crossvalidation)
286
Per class
Cross-validation details (10-fold Crossvalidation)
0.7215 ± 0.098
Per class
Cross-validation details (10-fold Crossvalidation)
0.7413 ± 0.0807
Cross-validation details (10-fold Crossvalidation)
0.8779 ± 0.0176
Cross-validation details (10-fold Crossvalidation)
0.8512 ± 0.0671
Cross-validation details (10-fold Crossvalidation)
0.457 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
0.4298 ± 0.0354
Cross-validation details (10-fold Crossvalidation)
0.9405 ± 0.077
Cross-validation details (10-fold Crossvalidation)
0.6224 ± 0.088
Cross-validation details (10-fold Crossvalidation)