现代信息科技2024，Vol.8Issue(18)：91-93,98,4.DOI:10.19850/j.cnki.2096-4706.2024.18.018
基于R语言算法及随机搜索的预测模型研究
Research on Prediction Model Based on R Language Algorithm and Random Search
摘要
Abstract
This paper uses Simple Random Sampling method,and divides the training set and the test set in a 7:3 ratio.Based on this training set,SVM,BP Neural Network,Decision Tree,Random Forest,Adaboost Algorithm,and Weighted K-nearest Neighbors classification models are established,and the test set is used to test the effect of the Heart Failure death risk prediction model.Accuracy,Recall Ratio,Precision Rate,Kappa coefficient,F1 score and other evaluation indexes are used to evaluate the prediction effect of various models after optimization.Finally,the BP Neural Network is selected as the best disease risk prediction model,which provides some reference opinions for clinical diagnosis of Heart Failure medical research.关键词
心力衰竭/随机搜索/预测模型/最优模型Key words
Heart Failure/Random Search/prediction model/optimum model分类
信息技术与安全科学引用本文复制引用
龙倩倩,唐兴芸..基于R语言算法及随机搜索的预测模型研究[J].现代信息科技,2024,8(18):91-93,98,4.基金项目
黔南州科技局2020年度黔南师院一流学科专项项目(2020Xk02St) （2020Xk02St）
