Run
1852855

Run 1852855

Task 145677 (Supervised Classification) Bioresponse Uploaded 17-03-2017 by Xiaolei Wang
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  • Fri_Mar_17_00.29.16_2017 NumPy_1.11.3. Python_3.5.2. run_task SciPy_0.18.1. sklearn.model_selection._search.GridSearchCV Sklearn_0.18.1.
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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.for est.RandomForestClassifier)(1)Automatically created sub-component.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrapTrue
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weightNone
sklearn.ensemble.forest.RandomForestClassifier(16)_criteriongini
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depthNone
sklearn.ensemble.forest.RandomForestClassifier(16)_max_featuresauto
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodesNone
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_scoreFalse
sklearn.ensemble.forest.RandomForestClassifier(16)_random_stateNone
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_cv10
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_error_scoreraise
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_estimatorRandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=-1, oob_score=False, random_state=None, verbose=0, warm_start=False)
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_fit_params{}
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_iidTrue
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_n_jobs-1
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_param_grid{'n_estimators': [32, 128, 1024], 'max_features': [1, 3, 5]}
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_pre_dispatch2*n_jobs
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_refitTrue
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_return_train_scoreTrue
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)(1)_scoringroc_auc
sklearn.model_selection._search.GridSearchCV(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
0.8739
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7959
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5884
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1360.4594
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3354
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4964
Cross-validation details (10-fold Crossvalidation)
Number of instances
3751
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7961
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7963
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.7963
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6756
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3879
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7786
Cross-validation details (10-fold Crossvalidation)