训练集 [计] training set
- 但是这些都是可以通过训练集估计求得。
They can, however, be estimated from the training set. - 你可以这样设想,并不是所有的训练集的输入都分类正确。
As you might imagine, not all training sets have the inputs classified correctly. - 这个原理的一个推论是,一种学习算法永远不会对它训练集的结果进行评估,因为对于一种未知的事例而言,没有证据表明算法具有概括它们的能力。
A corollary of this principle is that a learning algorithm should never be evaluated for its results in the training set because this shows no evidence of an ability to generalize to unseen instances.
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