Run
9204048

Run 9204048

Task 59 (Supervised Classification) iris Uploaded 29-06-2018 by Olivier Go
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(16)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(35)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(35)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(35)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(35)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(35)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(35)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(35)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(35)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(35)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(35)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(35)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(35)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(35)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(35)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(35)_random_state49617
sklearn.ensemble.forest.RandomForestClassifier(35)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(35)_warm_startfalse
sklearn.preprocessing.imputation.Imputer(20)_axis0
sklearn.preprocessing.imputation.Imputer(20)_copytrue
sklearn.preprocessing.imputation.Imputer(20)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(20)_strategy"median"
sklearn.preprocessing.imputation.Imputer(20)_verbose0
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(16)_memorynull
sklearn.preprocessing.data.OneHotEncoder(21)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(21)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(21)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(21)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(21)_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

0.9751 ± 0.0268
Per class
Cross-validation details (10-fold Crossvalidation)
0.9398 ± 0.059
Per class
Cross-validation details (10-fold Crossvalidation)
0.91 ± 0.0876
Cross-validation details (10-fold Crossvalidation)
132.6024 ± 0.8667
Cross-validation details (10-fold Crossvalidation)
0.0629 ± 0.0281
Cross-validation details (10-fold Crossvalidation)
0.4444
Cross-validation details (10-fold Crossvalidation)
150
Per class
Cross-validation details (10-fold Crossvalidation)
0.9428 ± 0.0562
Per class
Cross-validation details (10-fold Crossvalidation)
0.94 ± 0.0584
Cross-validation details (10-fold Crossvalidation)
1.585
Cross-validation details (10-fold Crossvalidation)
0.94 ± 0.0584
Per class
Cross-validation details (10-fold Crossvalidation)
0.1416 ± 0.0632
Cross-validation details (10-fold Crossvalidation)
0.4714
Cross-validation details (10-fold Crossvalidation)
0.1891 ± 0.0719
Cross-validation details (10-fold Crossvalidation)
0.4011 ± 0.1524
Cross-validation details (10-fold Crossvalidation)