Some enhancements of decision tree bagging
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For each audio file a large number of acoustic features were extracted using the openSMILE Feature Extractor Tool [15].. The configuration file emo_large.conf,
When discretization is performed (during decision tree construction), the table depends on the proposed attributes in the tree, and two different trees could infer two different
• pour chaque observation, on peut faire des prédictions avec les modèles provenant d’échantillon ne la contenant pas. On obtient l’erreur OOB associée au processus
– Breiman, random forests, machine learning 2001, (fourth rank top cited paper). – Breiman, bagging predictors, machine learning
