Run
8148695

Run 8148695

Task 119 (Learning Curve) zoo Uploaded 18-10-2017 by Toon Van Craenendonck
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Flow

TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator= sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(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"}}}
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_error_score"raise"
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_fit_params{}
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_iidtrue
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_iter5
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_jobs1
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_param_distributions{"bootstrap": [true, false], "criterion": ["gini", "entropy"], "max_depth": [3, null], "max_features": [1, 2, 3, 4], "min_samples_leaf": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "min_samples_split": [2, 3, 4, 5, 6, 7, 8, 9, 10]}
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_pre_dispatch"2*n_jobs"
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_random_state12172
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_refittrue
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_return_train_scoretrue
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_scoringnull
TESTf9d09de3dfsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_verbose0
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_bootstraptrue
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_class_weightnull
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_criterion"gini"
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_max_depthnull
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_max_features"auto"
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_max_leaf_nodesnull
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_min_impurity_split1e-07
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_min_samples_leaf1
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_min_samples_split2
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_min_weight_fraction_leaf0.0
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_n_estimators5
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_n_jobs1
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_oob_scorefalse
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_random_state33003
TESTf9d09de3dfsklearn.ensemble.forest.RandomForestClassifier(1)_verbose0
TESTf9d09de3dfsklearn.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.

17 Evaluation measures

Area under ROC curve
0.9937 ± 0.0123
Per class
F measure
0.9159 ± 0.0251
Per class
Kappa
0.8952 ± 0.1064
KB relative information score
830.3108 ± 0.8511
Mean absolute error
0.0497 ± 0.0229
Mean prior absolute error
0.2188 ± 0.0049
Number of instances
1010
Per class
Precision
0.9171 ± 0.0156
Per class
Predictive accuracy
0.9208 ± 0.0794
Prior entropy
2.4427
Recall
0.9208 ± 0.0794
Per class
Relative absolute error
0.2273 ± 0.1033
Root mean prior squared error
0.3294 ± 0.0075
Root mean squared error
0.1339 ± 0.0425
Root relative squared error
0.4064 ± 0.1265