I have a binary classifier. When i used my model to make predictions about 4k out of 10k were predicted to be "Rich". I am predicting affluence. Normally in classification the cut off to predict if class 1 is 0.5.
I have been asked to lower this to 0.4, but lowering it means FP increases and TPs also. How can I numerically display the 'cost' in moving the threshold lower than 0.5?