Machine Learning Fundamentals · 免费预览
训练优化的是什么，以及它无法做到什么
训练损失是在有限样本上求得的平均值，其最小值所处的参数值与期望损失的最小值所处的参数值并不相同，因此仅靠优化无法实现泛化。
1. Empirical risk and risk
Empirical risk and risk
2. Why stopping early is principled
Why stopping early is principled
3. Two kinds of stationary point
Two kinds of stationary point
4. Why the training loss can mislead
A model's training loss is driven to nearly zero by increasing its capacity, and its validation loss rises once the training loss is below a threshold. Which statement explains the divergence between the two losses?
5. The saddle point test
At a stationary point of a two-dimensional loss, the Hessian has eigenvalues and . The point is a ____.