摘要
Robotics&Machine Learning的新闻编辑每日新闻-支持向量机的新研究是一篇报道的主题。根据NewsRx记者在青岛的新闻报道，研究表明：“为了通过定量构效关系预测咔唑类化合物的抗锥虫作用，采用线性方法、随机森林法、径向基核函数支持向量机、线性组合混合核函数支持向量机建立了5个模型。”采用启发式方法和优化CatBoost方法分别选取两个不同的关键描述子集建立线性和非线性模型。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Support Vector Machine s is the subject of a report. According to news reporting from Qingdao, People’s Republic of China, by NewsRx journalists, research stated, “In order to predict the anti-trypanosome effect of carbazole-derived compounds by quantitative stru cture-activity relationship, five models were established by the linear method, random forest, radial basis kernel function support vector machine, linear combi nation mix-kernel function support vector machine, and nonlinear combination mix -kernel function support vector machine (NLMIX-SVM). The heuristic method and op timized CatBoost were used to select two different key descriptor sets for build ing linear and nonlinear models, respectively.”
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