Machine Learning Fundamentals · 免费预览
损失、训练集与验证集
训练需要一个数值化的目标函数以及对数据的划分，因为在已见数据上拟合得好与在未见数据上表现好并不是一回事。
1. The need for a number
The need for a number
2. Two common losses
Two common losses
3. The split that makes the number honest
The split that makes the number honest
4. Why the training loss is not the answer
A model with enough parameters fits the training set perfectly, driving the training error to zero, and performs poorly on new examples from the same source. Which statement explains the gap between the training error and the error on new examples?
5. The error rate is hard to optimize
For classification, the most direct objective is the error rate, the fraction of examples the model gets wrong. State the property of the error rate that makes it hard to minimize directly with gradient methods: it is ____.