Run
10228125

Run 10228125

Task 59 (Supervised Classification) iris Uploaded 17-05-2019 by Test Test
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(21)Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(36)_axis0
sklearn.preprocessing.imputation.Imputer(36)_copytrue
sklearn.preprocessing.imputation.Imputer(36)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(36)_strategy"median"
sklearn.preprocessing.imputation.Imputer(36)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(53)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(53)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(53)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(53)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(53)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(53)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(53)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(53)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(53)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(53)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(53)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(53)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(53)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(53)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(53)_random_state51322
sklearn.ensemble.forest.RandomForestClassifier(53)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(53)_warm_startfalse
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(21)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(21)_steps[{"oml-python:serialized_object": "component_reference", "value": {"step_name": "Imputer", "key": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"step_name": "OneHotEncoder", "key": "OneHotEncoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"step_name": "Classifier", "key": "Classifier"}}]
sklearn.preprocessing.data.OneHotEncoder(28)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(28)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(28)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(28)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(28)_sparsefalse

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
0.973 ± 0.0302
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9398 ± 0.059
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.91 ± 0.0876
Cross-validation details (10-fold Crossvalidation)
KB relative information score
132.9843 ± 0.9965
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0613 ± 0.0314
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9428 ± 0.0562
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.94 ± 0.0584
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.94 ± 0.0584
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1379 ± 0.0706
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1885 ± 0.0781
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3999 ± 0.1657
Cross-validation details (10-fold Crossvalidation)