Run
3404

Run 3404

Task 6 (Supervised Classification) anneal Uploaded 04-11-2019 by Test Test
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(3)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(7)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(7)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(7)_criterion"entropy"
sklearn.ensemble.forest.RandomForestClassifier(7)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(7)_max_features0.2
sklearn.ensemble.forest.RandomForestClassifier(7)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(7)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(7)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(7)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(7)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(7)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(7)_n_estimators16
sklearn.ensemble.forest.RandomForestClassifier(7)_n_jobsnull
sklearn.ensemble.forest.RandomForestClassifier(7)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(7)_random_state42
sklearn.ensemble.forest.RandomForestClassifier(7)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(7)_warm_startfalse
sklearn.impute._base.SimpleImputer(4)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(4)_copytrue
sklearn.impute._base.SimpleImputer(4)_fill_valuenull
sklearn.impute._base.SimpleImputer(4)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(4)_strategy"median"
sklearn.impute._base.SimpleImputer(4)_verbose0
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(3)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(3)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(3)_verbosefalse

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.

15 Evaluation measures

0.9861
Per class
Cross-validation details (33% Holdout set)
0.8465
Cross-validation details (33% Holdout set)
0.8209
Cross-validation details (33% Holdout set)
0.0358
Cross-validation details (33% Holdout set)
0.141
Cross-validation details (33% Holdout set)
0.9324
Cross-validation details (33% Holdout set)
296
Per class
Cross-validation details (33% Holdout set)
0.9324
Cross-validation details (33% Holdout set)
1.309
Cross-validation details (33% Holdout set)
0.2538
Cross-validation details (33% Holdout set)
0.2709
Cross-validation details (33% Holdout set)
0.1202
Cross-validation details (33% Holdout set)
0.4437
Cross-validation details (33% Holdout set)