| 乳腺癌预测模型构建研究 |
| 修订日期：2022-03-11 点此下载全文 |
| 引用本文：阮旭凌,刘琦,郭志恒,等.乳腺癌预测模型构建研究[J].医学信息学杂志,2022,43(5):34-39 |
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| 基金项目:科技创新2030——“新一代人工智能” 重大项目(批准号:2018AAA0102100)；湖南省教育厅科研重点项目“基于动态不确定因果图的证素辨证模型研究”(项目编号:18A219)；湖南省研究生创新课题“中医目诊信息数据元标准研究”(项目编号:CX2018B479)。 |
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| 中文摘要:在kaggle网站乳腺癌诊断数据集基础上,应用机器学习算法构建预测模型,阐述基本原理、模型建立方法,分析实验结果,指出降维处理后训练的预测模型分类准确率提高,其中基于XGBoost构建的预测模型分类效果最佳。 |
| 中文关键词:乳腺癌 降维 LDA XGBoost 分类 |
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| Study on the Construction of Breast Cancer Prediction Model |
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| Abstract:Based on the breast cancer diagnosis data set of the kaggle website, machine learning algorithms are used to construct prediction models, the basic principles and model building methods are expounded, and the experimental results are analyzed. The classification accuracy of the trained prediction model is improved after dimensionality reduction, and the classification effect of the prediction model built by XGBoost is better. |
| keywords:breast cancer dimension reduction LDA XGBoost classification |
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