Run
10155003

Run 10155003

Task 59 (Supervised Classification) iris Uploaded 23-03-2019 by Joaquin Vanschoren
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,Classifier=skle arn.ensemble.forest.RandomForestClassifier)(5)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(49)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(49)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(49)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(49)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(49)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(49)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(49)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(49)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(49)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(49)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(49)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(49)_n_estimators"warn"
sklearn.ensemble.forest.RandomForestClassifier(49)_n_jobsnull
sklearn.ensemble.forest.RandomForestClassifier(49)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(49)_random_state24615
sklearn.ensemble.forest.RandomForestClassifier(49)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(49)_warm_startfalse
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(5)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(5)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "OneHotEncoder", "step_name": "OneHotEncoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "Classifier", "step_name": "Classifier"}}]
sklearn.preprocessing.imputation.Imputer(39)_axis0
sklearn.preprocessing.imputation.Imputer(39)_copytrue
sklearn.preprocessing.imputation.Imputer(39)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(39)_strategy"median"
sklearn.preprocessing.imputation.Imputer(39)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(10)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(10)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(10)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(10)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(10)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(10)_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
0.9621 ± 0.0337
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8864 ± 0.033
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.83 ± 0.0483
Cross-validation details (10-fold Crossvalidation)
KB relative information score
110.2559 ± 0.9511
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1458 ± 0.0324
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
0.8864 ± 0.0332
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8867 ± 0.0322
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.8867 ± 0.0322
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.328 ± 0.073
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2503 ± 0.0408
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.531 ± 0.0865
Cross-validation details (10-fold Crossvalidation)