AI-900 Question #279: Real Exam Question with Answer & Explanation

The correct answer is D: Modify the threshold value in favor of false negatives.. If you have a classifier which calculates a real values score and then a threshold is applied to define what is classified as positive or negative. By changing this threshold you can decrease the number of false positives at the expense of increasing the number of false negatives

Submitted by dimitri_ru· Mar 30, 2026DOMAIN_LIST_NOT_PROVIDED

Question

What should you do to reduce the number of false positives produced by a machine learning classification model?

Options

AInclude test data in the training data.
BIncrease the number of training iterations.
CModify the threshold value in favor of false positives.
DModify the threshold value in favor of false negatives.

Explanation

If you have a classifier which calculates a real values score and then a threshold is applied to define what is classified as positive or negative. By changing this threshold you can decrease the number of false positives at the expense of increasing the number of false negatives.

Topics

#Machine learning model evaluation#Classification threshold#False positives#Model tuning

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