Run
7937315

Run 7937315

Task 59 (Supervised Classification) iris Uploaded 29-09-2017 by Wei-Sheng Chen
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(7)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(26)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(26)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(26)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(26)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(26)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(26)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(26)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(26)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(26)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(26)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(26)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(26)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(26)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(26)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(26)_random_state40581
sklearn.ensemble.forest.RandomForestClassifier(26)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(26)_warm_startfalse
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(7)_memorynull
sklearn.preprocessing.imputation.Imputer(10)_axis0
sklearn.preprocessing.imputation.Imputer(10)_copytrue
sklearn.preprocessing.imputation.Imputer(10)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(10)_strategy"median"
sklearn.preprocessing.imputation.Imputer(10)_verbose0
sklearn.preprocessing.data.OneHotEncoder(10)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(10)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(10)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(10)_n_values"auto"
sklearn.preprocessing.data.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

0.9735 ± 0.0307
Per class
Cross-validation details (10-fold Crossvalidation)
0.9466 ± 0.0423
Per class
Cross-validation details (10-fold Crossvalidation)
0.92 ± 0.0632
Cross-validation details (10-fold Crossvalidation)
132.4967 ± 0.8436
Cross-validation details (10-fold Crossvalidation)
0.0639 ± 0.0278
Cross-validation details (10-fold Crossvalidation)
0.4444
Cross-validation details (10-fold Crossvalidation)
150
Per class
Cross-validation details (10-fold Crossvalidation)
0.9485 ± 0.0402
Per class
Cross-validation details (10-fold Crossvalidation)
0.9467 ± 0.0422
Cross-validation details (10-fold Crossvalidation)
1.585
Cross-validation details (10-fold Crossvalidation)
0.9467 ± 0.0422
Per class
Cross-validation details (10-fold Crossvalidation)
0.1439 ± 0.0625
Cross-validation details (10-fold Crossvalidation)
0.4714
Cross-validation details (10-fold Crossvalidation)
0.1919 ± 0.0779
Cross-validation details (10-fold Crossvalidation)
0.4072 ± 0.1653
Cross-validation details (10-fold Crossvalidation)