Run
8148752

Run 8148752

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

TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator= sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
TEST8166236cf7sklearn.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"}}}
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_error_score"raise"
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_fit_params{}
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_iidtrue
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_iter5
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_jobs1
TEST8166236cf7sklearn.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]}
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_pre_dispatch"2*n_jobs"
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_random_state12172
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_refittrue
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_return_train_scoretrue
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_scoringnull
TEST8166236cf7sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_verbose0
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_bootstraptrue
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_class_weightnull
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_criterion"gini"
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_max_depthnull
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_max_features"auto"
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_max_leaf_nodesnull
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_min_impurity_split1e-07
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_min_samples_leaf1
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_min_samples_split2
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_min_weight_fraction_leaf0.0
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_n_estimators5
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_n_jobs1
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_oob_scorefalse
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_random_state33003
TEST8166236cf7sklearn.ensemble.forest.RandomForestClassifier(1)_verbose0
TEST8166236cf7sklearn.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