Run
18066

Run 18066

Task 119 (Supervised Classification) diabetes Uploaded 12-11-2019 by Continuous Integration
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  • openml-python Sklearn_0.22.dev0.
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Flow

TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklear n.ensemble._forest.RandomForestClassifier)(1)Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and "inverse_transform" if they are implemented in the estimator used. The parameters of the estimator used to apply these methods are optimized by cross-validated grid-search over a parameter grid.
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_cv{"oml-python:serialized_object": "cv_object", "value": {"name": "sklearn.model_selection._split.StratifiedKFold", "parameters": {"n_splits": "2", "random_state": "62501", "shuffle": "true"}}}
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_error_scoreNaN
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_iid"deprecated"
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_n_jobsnull
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_param_grid[{"max_features": [2, 4]}, {"min_samples_leaf": [1, 10]}]
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_pre_dispatch"2*n_jobs"
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_refittrue
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_return_train_scorefalse
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_scoringnull
TEST79c5ecfaecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)(1)_verbose0
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_bootstraptrue
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_ccp_alpha0.0
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_class_weightnull
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_criterion"gini"
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_max_depthnull
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_max_features"auto"
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_max_leaf_nodesnull
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_max_samplesnull
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_min_impurity_decrease0.0
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_min_impurity_splitnull
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_min_samples_leaf1
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_min_samples_split2
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_min_weight_fraction_leaf0.0
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_n_estimators5
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_n_jobsnull
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_oob_scorefalse
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_random_state33003
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_verbose0
TEST79c5ecfaecsklearn.ensemble._forest.RandomForestClassifier(1)_warm_startfalse

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.

arff
Trace

ARFF file with the trace of all hyperparameter settings tried during optimization, and their performance.

18 Evaluation measures

0.7593
Per class
Cross-validation details (10% Holdout set)
0.6945
Per class
Cross-validation details (10% Holdout set)
0.3378
Cross-validation details (10% Holdout set)
0.278
Cross-validation details (10% Holdout set)
0.3273
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.6957
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.6936
Per class
Cross-validation details (10% Holdout set)
0.6957
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.7131
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.4431
Cross-validation details (10% Holdout set)
0.9208
Cross-validation details (10% Holdout set)
0.6677
Cross-validation details (10% Holdout set)