Run
8148626

Run 8148626

Task 11 (Supervised Classification) balance-scale Uploaded 18-10-2017 by Toon Van Craenendonck
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Flow

sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemb le.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(29)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(29)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(29)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(29)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(29)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(29)_n_estimators5
sklearn.ensemble.forest.RandomForestClassifier(29)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(29)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(29)_random_state33003
sklearn.ensemble.forest.RandomForestClassifier(29)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(29)_warm_startfalse
sklearn.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"}}}
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_error_score"raise"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_fit_params{}
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_iidtrue
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_iter2
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_jobs1
sklearn.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]}
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_pre_dispatch"2*n_jobs"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_random_state12172
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_refittrue
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_return_train_scoretrue
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_scoringnull
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_verbose0

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
0.9357 ± 0.019
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8057 ± 0.0221
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6859 ± 0.0442
Cross-validation details (10-fold Crossvalidation)
KB relative information score
340.5439 ± 3.1396
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1718 ± 0.019
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3798 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Number of instances
625
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7857 ± 0.0258
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8272 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.3212
Cross-validation details (10-fold Crossvalidation)
Recall
0.8272 ± 0.0269
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4524 ± 0.0495
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4356 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2843 ± 0.0203
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6528 ± 0.0457
Cross-validation details (10-fold Crossvalidation)