Run
10194957

Run 10194957

Task 41 (Supervised Classification) soybean Uploaded 17-04-2019 by yang hua
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, estimator=sklearn.tree.tree.DecisionTreeClassifier)(13)Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(38)_axis0
sklearn.preprocessing.imputation.Imputer(38)_copytrue
sklearn.preprocessing.imputation.Imputer(38)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(38)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(38)_verbose0
sklearn.tree.tree.DecisionTreeClassifier(37)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(37)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(37)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(37)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(37)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(37)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(37)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(37)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(37)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(37)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(37)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(37)_random_state48439
sklearn.tree.tree.DecisionTreeClassifier(37)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(13)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(13)_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"}}]

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
0.9601 ± 0.0222
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9294 ± 0.0423
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.923 ± 0.0431
Cross-validation details (10-fold Crossvalidation)
KB relative information score
636.9132 ± 2.2067
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0074 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0961 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
683
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9306 ± 0.0387
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9297 ± 0.0393
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.8572
Cross-validation details (10-fold Crossvalidation)
Recall
0.9297 ± 0.0393
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.077 ± 0.0431
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2191 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.086 ± 0.0341
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3925 ± 0.1558
Cross-validation details (10-fold Crossvalidation)