Flat random forest: a new ensemble learning method towards better training efficiency and adaptive model size to deep forest
Crossref DOI link: https://doi.org/10.1007/s13042-020-01136-0
Published Online: 2020-05-09
Published Print: 2020-11
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Liu, Peng
Wang, Xuekui
Yin, Liangfei
Liu, Bing http://orcid.org/0000-0002-2365-6606
Funding for this research was provided by:
Fundamental Research Funds for the Central Universities (2017XKQY082)
Text and Data Mining valid from 2020-05-09
Version of Record valid from 2020-05-09
Article History
Received: 20 May 2019
Accepted: 2 May 2020
First Online: 9 May 2020