Run
9864490

Run 9864490

Task 59 (Supervised Classification) iris Uploaded 16-11-2018 by Lukas Brinkmeyer
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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_state51591
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

0.9748 ± 0.0309
Per class
0.9399 ± 0.0492
Per class
0.91 ± 0.0738
131.1819 ± 0.8648
0.0687 ± 0.0283
0.4444
150
Per class
0.941 ± 0.0487
Per class
0.94 ± 0.0492
Cross-validation details (10-fold Crossvalidation)
1.585
0.94 ± 0.0492
Per class
0.1546 ± 0.0636
0.4714
0.1907 ± 0.0697
0.4045 ± 0.1478