Run
8858075

Run 8858075

Task 146817 (Supervised Classification) steel-plates-fault Uploaded 21-02-2018 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.tree.tree.DecisionTreeClassifier)(4)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.tree.tree.DecisionTreeClassifier(19)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(19)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(19)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(19)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(19)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(19)_min_impurity_split1e-07
sklearn.tree.tree.DecisionTreeClassifier(19)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(19)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(19)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(19)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(19)_random_state3057
sklearn.tree.tree.DecisionTreeClassifier(19)_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
0.8081 ± 0.0169
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7119 ± 0.0243
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6294 ± 0.0321
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1310.757 ± 5.5369
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0824 ± 0.0072
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
0.7127 ± 0.0239
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7115 ± 0.0251
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.4138
Cross-validation details (10-fold Crossvalidation)
Recall
0.7115 ± 0.0251
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3707 ± 0.0322
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
0.2871 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8612 ± 0.0372
Cross-validation details (10-fold Crossvalidation)