Run
10460027

Run 10460027

Task 3711 (Supervised Classification) elevators Uploaded 20-05-2020 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._data.StandardScaler ,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.preprocessing._data.StandardScaler(1)_copyfalse
sklearn.preprocessing._data.StandardScaler(1)_with_meanfalse
sklearn.preprocessing._data.StandardScaler(1)_with_stdtrue
sklearn.tree._classes.DecisionTreeClassifier(3)_ccp_alpha0.19361987617262622
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth10
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features0.02806876990410797
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes5426
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease0.08528974060996027
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_splitnull
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf0.30273088346206883
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split0.04032386951945634
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf0.043772535099489085
sklearn.tree._classes.DecisionTreeClassifier(3)_presort"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter"best"
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.StandardScaler,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.StandardScaler,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._data.StandardScaler,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

0.5
Per class
Cross-validation details (10-fold Crossvalidation)
0 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4271 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4271 ± 0
Cross-validation details (10-fold Crossvalidation)
0.6909 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
16599
Per class
Cross-validation details (10-fold Crossvalidation)
0.6909 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8921 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4621 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4621 ± 0
Cross-validation details (10-fold Crossvalidation)
1 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5
Cross-validation details (10-fold Crossvalidation)