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.

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。

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Current intrusion detection systems lack the ability to generalize from previously observed attacks to detect even slight variations of known attacks.

现存的入侵检测系统缺乏从先前所观测到的进攻进行概括并检测已知攻击的细微变化的能力。

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