摘要
宫颈癌是世界上严重危害女性健康的恶性肿瘤之一,所幸的是,这种疾病是可以预防的。预防或早期发现是一个具有挑战性的难题,本文利用Lasso方法、Adaptive Lasso方法、Elastic net方法和Adaptive Elastic net方法通过宫颈癌行为风险数据集建立Logistic模型,以帮助进行宫颈癌早期检测和筛查。从实验结果看,Lasso方法表现更优。
Cervical cancer is one of the malignant tumors that seriously endanger women’s health in the world. Fortunately, this disease can be prevented. Prevention or early detection is a challenging problem. In this paper, in order to help early detection and screening of cervical cancer, we consider the Lasso, adaptive Lasso, elastic net and adaptive elastic net to establish a logistic model through the behavioral risk data set of cervical cancer. From the experimental results, Lasso procedure has good performance.
出处
《应用数学进展》
2022年第2期781-789,共9页
Advances in Applied Mathematics
