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Analyzing Health Seeking Behavior of Chinese Residents and Their Influencing Factors Based on CHNS Data

机译:基于CHNS数据的中国居民健康寻求行为及其影响因素分析

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With the improvement of people’s living standards, Chinese residents have paid more and more attention to health. The development of science and technology has made medical health big data emerge and has gradually become a research hotspot. In our paper, we first adopted Logistic Regression to find out the important variables for health seeking behavior and then we verified that this behavior can be predicted based on machine learning algorithms. By comparing classic Support Vector Machine (SVM) algorithm and improved SVM model with different variables, we finally proposed a SVM model based on SMOTE algorithm that is relatively optimal for predicting health seeking behavior.
机译:随着人民生活水平的提高,中国居民越来越重视健康。科技的发展使医疗卫生大数据应运而生,并逐渐成为研究热点。在本文中,我们首先采用Logistic回归来找出健康寻求行为的重要变量,然后验证了可以基于机器学习算法预测此行为。通过比较经典的支持向量机(SVM)算法和改进的具有不同变量的SVM模型,我们最终提出了一种基于SMOTE算法的SVM模型,该模型对于预测健康状况是相对最佳的。

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