Link : https://www.zhihu.com/question/30643044/answer/48955833
Source: Zhihu
The following are two scenarios:
1. Earthquake prediction
For earthquake prediction, we hope that the RECALL is very high, that is to say, we want to predict every earthquake. This time we can sacrifice PRECISION. Better to sound 1,000 alarms and predict 10 earthquakes correctly; don't predict 8 times 100 times and miss two.
2. The conviction of the suspect is
based on the principle of not blaming a good person. We hope that the conviction of the suspect is very accurate. Time to spare some criminals sometimes (low recall), but it's worth it.
For the classifier, it is essentially to give a probability. At this time, we choose a CUTOFF point (threshold), which is higher than this point and judged to be negative. Then the choice of this point needs to be selected according to your specific scene. In turn, the scene will determine the standard when training the model. For example, in the first scene, we only look at the PRECISION when RECALL=99.9999% (the earthquake is all in), and other indicators become meaningless.
If you can only choose one indicator, it must be PRC. A model can be seen clearly.