Question

You have built a classification model with 90% accuracy but your client is not happy
Because False Positive rate was very high then what will you do?

Answer 1

Explanation:

False positive rate is an event metric that signifies the probability of the classification model to falsely reject the null hypothesis for a particular observation. In order to bring down the percentage of false positive ratio, the sensitivity and the specificity of the model needs to be enhanced so that the prospects of showing an erroneous result is reduced to minimum.