How to choose threshold for binary classification

1. How do you choose a threshold for a binary classifier?
2. How do you choose a threshold value?
3. How do you choose a threshold in logistic regression?

How do you choose a threshold for a binary classifier?

In binary classification, when a model gives us a score instead of the prediction itself, we usually need to convert this score into a prediction applying a threshold. Since the meaning of the score is to give us the perceived probability of having 1 according to our model, it's obvious to use 0.5 as a threshold.

How do you choose a threshold value?

To find the right threshold for your application, first you need to collect a representative set of images. The set of images should be representative, not just with regard to their number, but in the quality and types of the images that may be encountered in the stream.

How do you choose a threshold in logistic regression?

The logistic regression assigns each row a probability of bring True and then makes a prediction for each row where that prbability is >= 0.5 i.e. 0.5 is the default threshold.