Scholarlink

<p>Cardiovascular disease is a significant and severe disease that causes a high percentage of morbidity and accounts for nearly one-third of all fatalities. With the changing lifestyle of people and consumption of low-nutrient foods in today’s time leads to high-risk factors of cardiovascular disease. Thus, it is required to predict cardiovascular disease and take precautions timely. Various experiments have been performed to detect and prevent cardiovascular disease by many researchers. In this paper, we have presented a method based on XGBoost and OPTUNA hyper-parameter to detect cardiovascular disease. XGBoost is a machine learning algorithm that gives better performance and OPTUNA is an automatic hyper-parameter optimization software framework. We have achieved 96.77% and 93.52% accuracy on the UCI Cleveland dataset and Kaggle Heart Failure dataset respectively.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Prediction of Cardiovascular Disease using XGBoost with OPTUNA

  • 期刊论文

  • 发表日期：

    2025年4月25日

查看全文
  • Anamika Jain,
  • Akansha Singh,
  • Aman Doherey

摘要

Cardiovascular disease is a significant and severe disease that causes a high percentage of morbidity and accounts for nearly one-third of all fatalities. With the changing lifestyle of people and consumption of low-nutrient foods in today’s time leads to high-risk factors of cardiovascular disease. Thus, it is required to predict cardiovascular disease and take precautions timely. Various experiments have been performed to detect and prevent cardiovascular disease by many researchers. In this paper, we have presented a method based on XGBoost and OPTUNA hyper-parameter to detect cardiovascular disease. XGBoost is a machine learning algorithm that gives better performance and OPTUNA is an automatic hyper-parameter optimization software framework. We have achieved 96.77% and 93.52% accuracy on the UCI Cleveland dataset and Kaggle Heart Failure dataset respectively.