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In addition, we propose the\u00a0Data-driven Multinomial Random Forest (DMRF)\u00a0algorithm, which has the same complexity with BreimanRF (proposed by Breiman) while satisfying strong consistency with probability 1. It has better performance in classification and regression tasks than previous RF variants that only satisfy weak consistency, and in most cases even surpasses BreimanRF in classification tasks. To the best of our knowledge, DMRF is currently a low-complexity and high-performing variation of random forest that achieves strong consistency with probability 1.<\/jats:p>","DOI":"10.1186\/s40537-023-00874-6","type":"journal-article","created":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T17:02:19Z","timestamp":1708707739000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Data-driven multinomial random forest: a new random forest variant with strong consistency"],"prefix":"10.1186","volume":"11","author":[{"given":"JunHao","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"XueLi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,23]]},"reference":[{"issue":"1","key":"874_CR1","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L. 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