# 1.12 改善你的模型的表现（Improving your model performance）

提高机器学习模型性能主要要解决两个问题：avoidable bias和variance。training error与human-level error之间的差值反映的是avoidable bias，dev error与training error之间的差值反映的是variance

**基本假设：**

* 模型在训练集上有很好的表现；
* 模型推广到开发和测试集啥也有很好的表现

**减少可避免偏差**

* 训练更大的模型
* 训练更长时间、训练更好的优化算法（Momentum、RMSprop、Adam）
* 寻找更好的网络架构（RNN、CNN）、寻找更好的超参数

**减少方差**

* 收集更多的数据
* 正则化（L2、dropout、数据增强）
* 寻找更好的网络架构（RNN、CNN）、寻找更好的超参数

![](/files/-Le0cdgHaDu6QmsE-H6-)![](/files/-Le0cdgJf93zn3vvUP29)


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