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    "Boosting 算法的工作机制如下：先从初始训练集训练出一个基学习器，再根据基学习器的表现对训练样本分布进行调整，使得之前错误分类的样本在后续受到更多关注，然后基于调整后的样本分布来训练下一个基学习器，直到基学习器数目达到预设的 T，最终将这 T 个基学习器进行加权结合。\n",
    "\n",
    "Boosting 的代表算法是 AdaBoost。"
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