wee6——模型评估

Posted 2021-11-05 ^_^|

训练集、测试集、验证集

One way to break down our dataset into the three sets is:

1. Training set: 60%
2. Cross validation set: 20%
3. Test set: 20%

三种数据划分可以分别做一下用途：
We can now calculate three separate error values for the three different sets using the following method:

1. Optimize the parameters in Θ using the training set for each polynomial degree.
2. Find the polynomial degree d with the least error using the cross validation set.
3. Estimate the generalization error using the test set with $J_{test}({\Theta }^{(d)})$
   (d = theta from polynomial with lower error);

如果只是按照训练集、测试集进行划分，那么测试集就承担了完成2、3两步的任务，但是第二步就是用测试集去选择的d，如果第三步再用测试集去评估模型，很显然是“不公平”的。因此，我们引入了验证集去分担任务2.