控制理论与应用2021，Vol.38Issue(10)：1503-1510,8.DOI:10.7641/CTA.2021.10060
基于多分类算法混合比较的乳腺癌预测
Breast cancer prediction based hybrid comparison of multiple classification algorithms
摘要
Abstract
Breast cancer is an important cause of the death of female cancer patients due to its easy recurrence and high mortality. Early diagnosis of breast cancer increases the probability of curing cancer. Therefore, it is particularly important to improve the accuracy of early diagnosis. The traditional early diagnosis mainly relies on human experience to judge breast cancer by analyzing clinical or examination data, and sufficient accuracy cannot be guaranteed. Many researchers have proposed various machine learning methods to improve prediction accuracy and efficiency. However, the current algorithms have high computational complexity, and it is difficult to directly determine the appropriate algorithm from a variety of algorithms. This paper experiments with ten popular classification algorithms, compares the differences between the algorithms, and applies quantum support vector machines to speed up the computation process. Numerical experiments show that support vector machines and artificial neural network achieve the best prediction results, verifying the effectiveness of hybrid comparison of multiple classification algorithms.关键词
乳腺癌/支持向量机/分类/量子计算Key words
breast cancer/support vector machines/classification/quantum computing引用本文复制引用
李莉,汪咏,陆宁,林国义..基于多分类算法混合比较的乳腺癌预测[J].控制理论与应用,2021,38(10):1503-1510,8.基金项目
Supported by the National Key R&D Program of China(2018YFE0105000,2018YFB1305304),the Shanghai Municipal Science and Technology Major Project under grant(2021SHZDZX0100)and the Shanghai Municipal Commission of Science and Technology(1951113210,19511132101). （2018YFE0105000,2018YFB1305304）
