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Heart Disease Prediction Model Based on Model Ensemble

机译:基于模型集合的心脏病预测模型

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With the increase of heart disease patients in the current society, early prevention of the heart health has become the top priority. The paper proposed a new heart disease prediction method based on model ensemble, which combined three independent models including SVM, decision tree and ANN. As for the data source, the public dataset published by UCI has been preprocessed and used into the combined model and three individual models. The prediction effect has been evaluated by accuracy, precision, recall, and f1 score indicators. As the result shown, compared with three independent models, the ensemble model has a better performance generally indicating a practical medical use.
机译:随着当前社会中心脏病患者的增加,预防心脏健康状况已成为首要任务。 本文提出了一种基于模型集合的新型心脏病预测方法,其组合了三种独立模型,包括SVM,决策树和ANN。 至于数据源,UCI发布的公共数据集已被预处理并用于组合模型和三个单独模型。 通过精度,精度,召回和F1分数指示器评估了预测效果。 随着结果所示,与三种独立模型相比,集合模型具有更好的性能,通常表明实际使用。

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