使用克利夫兰心脏病数据集包含 的303个实例和14个属性，请直接使用克利夫兰心脏病数据集的目标变量基于随机森林模型进行二分类预测，预测患者是否会患上心脏病。基 于6个方法（混淆矩阵，精度，召回率、精确率和 F1 分数，ROC 曲线和 AUC 分数，特征重要性，部分依赖图）对前面随机森林模型的预测结果进行评估和解释。
☆10Jul 17, 2024Updated 2 years ago
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