I used boosted regression trees on a dataset I was working on to predict how much a customer will spend in a given year. Here is a sample of the output:
Person Actual Predicted 1 500 400 2 300 100 3 2000 1900 4 5 0 5 100000 60000
I would like to assess the accuracy of the model. However, if I compute the square root of MSE, I get 8981.54, which is too large for customers that will not spend anywhere close to this value. I then tried to compute a correlation coefficient between the two columns, and I get 0.999, which I'm not sure if it is a possible alternative? Any suggestions here?