OpenML
10228676

Run 10228676

Task 146817 (Supervised Classification) steel-plates-fault Uploaded 16-06-2019 by joe zhou
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.tree.tree.DecisionTreeClassifier)(1)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"mean"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(1)_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.tree.DecisionTreeClassifier)(1)_verbosefalse
sklearn.tree.tree.DecisionTreeClassifier(43)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(43)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(43)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(43)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(43)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(43)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(43)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(43)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(43)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(43)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(43)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(43)_random_state42278
sklearn.tree.tree.DecisionTreeClassifier(43)_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.

17 Evaluation measures

Area under ROC curve
0.8112 ± 0.0161
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7169 ± 0.0237
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6351 ± 0.0288
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.6796 ± 0.0236
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0811 ± 0.0064
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2223 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Number of instances
1941
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.718 ± 0.0242
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7161 ± 0.0224
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.4107 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
Recall
0.7161 ± 0.0224
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3648 ± 0.0287
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3334 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2848 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8543 ± 0.0333
Cross-validation details (10-fold Crossvalidation)