How would you choose a classification threshold?

Q: How would you choose a classification threshold?

This question evaluates understanding of threshold selection for probabilistic binary classifiers, testing competencies in validation-set decision threshold choice, cost-sensitive trade-offs between false positives and false negatives, effects of class imbalance, and probability calibration.

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Question

You trained a binary classifier that outputs a probability score p(y=1|x). You must choose a decision threshold t to convert probabilities into class labels.

Answer the following:

What is your general approach to selecting t on a validation set?
How do you incorporate different costs of false positives vs false negatives?
How do class imbalance and probability calibration affect threshold choice?
Give one example where you would prefer a high threshold and one where you would prefer a low threshold.

How would you choose a classification threshold?

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Solution

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