The Random Forest (RF) model consists of an ensemble classifier that produces many decision trees through the use of a randomly selected subset of samples and training variables. The RF model has assumed importance within the scientific community thanks to its performance. The accuracy of its classifications and prediction has allowed the use of RF in several research domains, which have benefited from it. The present study aims to provide a preliminary review of the whole sci- entific production characterized by all the publications citing the article ”Random Forest” by Breiman, 2001, in the last 20 years (2001-2021).

Twenty Years of Random Forest: preliminary results of a systematic literature review / Aria, Massimo; Gnasso, Agostino; D’Aniello, Luca. - (2022), pp. 225-230. (Intervento presentato al convegno IES 2022 Innovation & Society 5.0: Statistical and Economic Methodologies for Quality Assessment).

Twenty Years of Random Forest: preliminary results of a systematic literature review

Massimo Aria;Agostino Gnasso;Luca D’Aniello
2022

Abstract

The Random Forest (RF) model consists of an ensemble classifier that produces many decision trees through the use of a randomly selected subset of samples and training variables. The RF model has assumed importance within the scientific community thanks to its performance. The accuracy of its classifications and prediction has allowed the use of RF in several research domains, which have benefited from it. The present study aims to provide a preliminary review of the whole sci- entific production characterized by all the publications citing the article ”Random Forest” by Breiman, 2001, in the last 20 years (2001-2021).
2022
9788894593365
Twenty Years of Random Forest: preliminary results of a systematic literature review / Aria, Massimo; Gnasso, Agostino; D’Aniello, Luca. - (2022), pp. 225-230. (Intervento presentato al convegno IES 2022 Innovation & Society 5.0: Statistical and Economic Methodologies for Quality Assessment).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/895688
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