乳腺癌风险因素分析和生存预测的监督式机器学习（英文版）

英文标题：Supervised Machine Learning for Breast Cancer Risk Factors Analysis and Survival Prediction中文摘要：利用机器学习方法，比较逻辑回归、支持向量机、决策树、随机森林、极端随机树、最近邻算法和自适应增强等七种分类模型来预测基于 METABRIC 数据集中 1904 名患者记录的 5 年乳腺癌生存率。研究结果表明，这些分类器可以准确预测样品的生存率，分别为 75.4％，74.7％，71.5％，75.5％，70.3％和 78％英文摘要：The choice of the most effective treatment may eventually be influenced bybreast cancer survival prediction. To predict the chances of a patientsurviving, a variety of techniques were employed, such as statistical, machinelearning, a