Run
10464966

Run 10464966

Task 14954 (Supervised Classification) cylinder-bands Uploaded 20-07-2020 by Sean Broestl
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, decisiontreeclassifier=sklearn.tree._classes.DecisionTreeClassifier)(1)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.impute._base.SimpleImputer(16)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(16)_copytrue
sklearn.impute._base.SimpleImputer(16)_fill_valuenull
sklearn.impute._base.SimpleImputer(16)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(16)_strategy"mean"
sklearn.impute._base.SimpleImputer(16)_verbose0
sklearn.tree._classes.DecisionTreeClassifier(5)_ccp_alpha0.0
sklearn.tree._classes.DecisionTreeClassifier(5)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(5)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(5)_max_depthnull
sklearn.tree._classes.DecisionTreeClassifier(5)_max_featuresnull
sklearn.tree._classes.DecisionTreeClassifier(5)_max_leaf_nodesnull
sklearn.tree._classes.DecisionTreeClassifier(5)_min_impurity_decrease0.0
sklearn.tree._classes.DecisionTreeClassifier(5)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(5)_min_samples_leaf1
sklearn.tree._classes.DecisionTreeClassifier(5)_min_samples_split2
sklearn.tree._classes.DecisionTreeClassifier(5)_min_weight_fraction_leaf0.0
sklearn.tree._classes.DecisionTreeClassifier(5)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(5)_random_state43148
sklearn.tree._classes.DecisionTreeClassifier(5)_splitter"best"
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,decisiontreeclassifier=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,decisiontreeclassifier=sklearn.tree._classes.DecisionTreeClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,decisiontreeclassifier=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbosefalse

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

0.7102 ± 0.0695
Per class
Cross-validation details (10-fold Crossvalidation)
0.7193 ± 0.0689
Per class
Cross-validation details (10-fold Crossvalidation)
0.4231 ± 0.141
Cross-validation details (10-fold Crossvalidation)
0.4208 ± 0.1413
Cross-validation details (10-fold Crossvalidation)
0.2796 ± 0.0684
Cross-validation details (10-fold Crossvalidation)
0.4879 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.7204 ± 0.0684
Cross-validation details (10-fold Crossvalidation)
540
Per class
Cross-validation details (10-fold Crossvalidation)
0.7189 ± 0.0697
Per class
Cross-validation details (10-fold Crossvalidation)
0.7204 ± 0.0684
Cross-validation details (10-fold Crossvalidation)
0.9825 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
0.5731 ± 0.1399
Cross-validation details (10-fold Crossvalidation)
0.4939 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.5288 ± 0.0663
Cross-validation details (10-fold Crossvalidation)
1.0706 ± 0.1335
Cross-validation details (10-fold Crossvalidation)
0.7102 ± 0.0695
Cross-validation details (10-fold Crossvalidation)