Run
10454992

Run 10454992

Task 3735 (Supervised Classification) pollen Uploaded 19-05-2020 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=sklearn.preprocessing._discretization.KBin sDiscretizer,step_1=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.tree._classes.DecisionTreeClassifier(3)_ccp_alpha0.9676839726636844
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth82
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features0.9257389219067881
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes2844
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.16938250465534974
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.21071484942546828
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.20657255446817513
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.3677726278513144
sklearn.tree._classes.DecisionTreeClassifier(3)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter"best"
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_encode"onehot"
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_n_bins58
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_strategy"uniform"
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,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=sklearn.preprocessing._discretization.KBinsDiscretizer,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.

18 Evaluation measures

0.4988
Per class
Cross-validation details (10-fold Crossvalidation)
0.4939
Per class
-0.0021
-0 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)
0.499 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
3848
Per class
Cross-validation details (10-fold Crossvalidation)
0.4989
Per class
0.499 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
1
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)
0.5 ± 0
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.499
Cross-validation details (10-fold Crossvalidation)