机器学习算法用于乳腺癌检测的性能研究

Research on the Performance of Machine Learning Algorithm in Breast Cancer Detection

乳腺癌排在女性恶性肿瘤首位,早期发现和诊断是治疗的关键。使用开源乳腺癌数据集,使用了K-近邻、逻辑回归、支持向量机等主流机器学习算法对数据集进行了大量的训练和测试,分析了它们在训练过程中的学习曲线,对训练和测试结果进行了对比,分析和研究了这些算法在乳腺癌检测中的性能,并对未来的研究方向和技术进行了展望。

Breast cancer ranks the first among female malignant tumors, because the early stage does not have typical symptoms and characteristics and is easy to cause neglect, early detection and diagnosis is the key to improve the curative effect. In this paper, open source breast cancer data sets are used, and KNN, logistic regression and SVM machine learning algorithms are used to compare the training results of data sets, and the performance of these machine learning algorithms in breast cancer detection is analyzed and studied. The future research direction and technology are also prospected.