Comments (1)
ruyiluo
commented on May 20, 2024
有一种经验说法认为boosting对过拟合有一定的稳健性，不太容易过拟合，泛化能力不错。这种稳健性不是源于boosting(boosting本身是会加剧overfit的），而是源于弱模型合成（加权平均）过程中的“投票”效果，而且，我们总是可以使用交叉验证，及时停止boosting，避免合成过多的模型
参考链接：https://zhuanlan.zhihu.com/p/517900957
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