Analysis of influencing factors of heart disease based on XGBoost and SHAP
Heart disease is a common and serious disease that seriously affects people's health and quality of life.In recent years,the prediction and analysis of heart disease have received widespread attention.With the development of machine learning and data science,more and more research is using these methods to construct predictive models and analysis methods for heart disease.The article proposes a heart disease prediction model based on data analysis and machine learning algorithms,evaluates the factors affecting heart disease by constructing a logistic regression model,and conducts empirical research.The results show that the constructed model performs well in predicting the influencing factors of heart disease and has stability.
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