If he infers that she is interested when she is in fact not interested, then he has made an error of false positive (what the statisticians call the "Type I" error).
如果他推断说，她感兴趣，而她其实上不感兴趣，那么他犯了假阳性的错误(统计人员所谓的“第一类”错误)。
So we make two types of errors: a type I error, or false positive, is believing a pattern is real when it is not; a type II error, or false negative, is not believing a pattern is real when it is.
因此我们常犯两类错误：第一类，是虚假的肯定，当原型并不存在时它认为原型是真的；第二类，是虚假的否定，当原型存在时它却认为原型是虚假的。
In the experiment, we analyze the system error rate of positive rate and false negative.
在实验中，对系统的错误肯定率和错误否定率进行了分析。
The experimental results show that the model features high detection rates and low false-positive error rates.
实验结果表明，该模型具有较高的检测率并降低了误报率。
They don't know what's actually happening under the covers and how severe the error is so you could argue that it's a false-positive.
他们不知道什么是实际发生在被窝是多么严重的错误是你能认为这是一个假阳性。
They don't know what's actually happening under the covers and how severe the error is so you could argue that it's a false-positive.
他们不知道什么是实际发生在被窝是多么严重的错误是你能认为这是一个假阳性。
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