Run
9864488

Run 9864488

Task 59 (Supervised Classification) iris Uploaded 16-11-2018 by Randolf Scholz
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(19)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(41)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(41)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(41)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(41)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(41)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(41)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(41)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(41)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(41)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(41)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(41)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(41)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(41)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(41)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(41)_random_state65268
sklearn.ensemble.forest.RandomForestClassifier(41)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(41)_warm_startfalse
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(19)_memorynull
sklearn.preprocessing.imputation.Imputer(26)_axis0
sklearn.preprocessing.imputation.Imputer(26)_copytrue
sklearn.preprocessing.imputation.Imputer(26)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(26)_strategy"median"
sklearn.preprocessing.imputation.Imputer(26)_verbose0
sklearn.preprocessing.data.OneHotEncoder(26)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(26)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(26)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(26)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(26)_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
0.9727 ± 0.0298
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9332 ± 0.0633
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9 ± 0.0943
Cross-validation details (10-fold Crossvalidation)
KB relative information score
130.7144 ± 0.9869
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0693 ± 0.0303
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
0.9351 ± 0.0618
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9333 ± 0.0629
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9333 ± 0.0629
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1559 ± 0.0683
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1972 ± 0.0732
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4183 ± 0.1552
Cross-validation details (10-fold Crossvalidation)