Run
10462467

Run 10462467

Task 3891 (Supervised Classification) gina_agnostic Uploaded 21-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
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Flow

sklearn.pipeline.Pipeline(step_0=automl.components.data_preprocessing.imput ation.ImputationComponent,step_1=sklearn.tree._classes.DecisionTreeClassifi er)(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.tree._classes.DecisionTreeClassifier(3)_ccp_alpha0.950063364501545
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth38
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features0.8717598971253634
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes596
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.17145697876693203
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.4278637199401998
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.21263196128732076
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.48269279511954477
sklearn.tree._classes.DecisionTreeClassifier(3)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter"best"
automl.components.data_preprocessing.imputation.ImputationComponent(1)_add_indicatortrue
automl.components.data_preprocessing.imputation.ImputationComponent(1)_missing_valuesNaN
automl.components.data_preprocessing.imputation.ImputationComponent(1)_strategy"most_frequent"
sklearn.pipeline.Pipeline(step_0=automl.components.data_preprocessing.imputation.ImputationComponent,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=automl.components.data_preprocessing.imputation.ImputationComponent,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=automl.components.data_preprocessing.imputation.ImputationComponent,step_1=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.

16 Evaluation measures

0.4987
Per class
Cross-validation details (10-fold Crossvalidation)
-0 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5084 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
3468
Per class
Cross-validation details (10-fold Crossvalidation)
0.5084 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
0.9998 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4999 ± 0
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)