Run
10464903

Run 10464903

Task 145677 (Supervised Classification) Bioresponse Uploaded 18-07-2020 by Jerry Ebalunode
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.tree._classes.DecisionTreeClassifier)(4)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)(4)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier)(4)_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)(4)_verbosefalse
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_state41824
sklearn.tree._classes.DecisionTreeClassifier(5)_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

0.7314 ± 0.0272
Per class
Cross-validation details (10-fold Crossvalidation)
0.7336 ± 0.0264
Per class
Cross-validation details (10-fold Crossvalidation)
0.4631 ± 0.0536
Cross-validation details (10-fold Crossvalidation)
0.4618 ± 0.0528
Cross-validation details (10-fold Crossvalidation)
0.2663 ± 0.0261
Cross-validation details (10-fold Crossvalidation)
0.4964 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.7337 ± 0.0261
Cross-validation details (10-fold Crossvalidation)
3751
Per class
Cross-validation details (10-fold Crossvalidation)
0.7335 ± 0.0265
Per class
Cross-validation details (10-fold Crossvalidation)
0.7337 ± 0.0261
Cross-validation details (10-fold Crossvalidation)
0.9948 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.5365 ± 0.0526
Cross-validation details (10-fold Crossvalidation)
0.4982 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.5161 ± 0.0259
Cross-validation details (10-fold Crossvalidation)
1.0358 ± 0.0519
Cross-validation details (10-fold Crossvalidation)
0.7314 ± 0.0272
Cross-validation details (10-fold Crossvalidation)