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In this paper, we focus on the reaction yield prediction problem, which assists chemists in selecting high-yield reactions in a new chemical space only with a few experimental trials. To attack this challenge, we first put forth MetaRF, an attention-based random forest model specially designed for the few-shot yield prediction, where the attention weight of a random forest is automatically optimized by the meta-learning framework and can be quickly adapted to predict the performance of new reagents while given a few additional samples. To improve the few-shot learning performance, we further introduce a dimension-reduction based sampling method to determine valuable samples to be experimentally tested and then learned. Our methodology is evaluated on three different datasets and acquires satisfactory performance on few-shot prediction. In high-throughput experimentation (HTE) datasets, the average yield of our methodology\u2019s top 10 high-yield reactions is relatively close to the results of ideal yield selection.<\/jats:p>","DOI":"10.1186\/s13321-023-00715-x","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T09:03:14Z","timestamp":1681117394000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["MetaRF: attention-based random forest for reaction yield prediction with a few trails"],"prefix":"10.1186","volume":"15","author":[{"given":"Kexin","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangyong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyou","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuansheng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ercheng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingjun","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pheng-Ann","family":"Heng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,4,10]]},"reference":[{"issue":"3902","key":"715_CR1","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1126\/science.166.3902.178","volume":"166","author":"EJ Corey","year":"1969","unstructured":"Corey EJ, Wipke WT (1969) Computer-assisted design of complex organic syntheses: pathways for molecular synthesis can be devised with a computer and equipment for graphical communication. 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