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习题10-3 #72

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simo-an opened this issue Jan 25, 2022 · 0 comments

simo-an commented Jan 25, 2022

习题10-3 分析自训练和EM算法之间的联系

解答

什么是自训练
首先使用标注数据训练一个模型 => 使用该模型来预测无标签样本的标签 => 将置信度较高的样本连同预测的标签加入到训练集 => 重新训练模型 => ...

不断循环上面的过程。

EM算法简介
EM算法分为两步，即 E步和M步：

E 步：当参数 𝜃 已知 => 根据训练数据推断出最优隐变量的值
M步：当隐变量已知 => 对参数 𝜃 做极大似然估计

这两步不断重复，直到收敛到某个局部最优解．

自训练和EM算法之间的联系
自训练和密度估计中 EM 算法都是通过不断地迭代来提高模型能力

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