I tried visualizing but I don’t know how that helps me construct a formula. I would imagine, in your example, the landscape would be mountainous. One movie may have both great suspense and great humor and be a great movie...another may have both great suspense and great humor and be just an okay movie. But then perhaps there is a movie with very low amounts of humor or suspense that is still a good movie for other reasons. So in that case neither of these metrics would be good predictors for that movie.
That’s kind of the core of the issue, as your exercise illustrates. Since in any given case, and metric can be a complete non-predictor of the outcome, I don’t know any way to construct the formula. It seems like you’d have to find some way to both include and exclude metrics based on (something).
So maybe the answer is the N/A thing I considered. Valuing movie metrics is not about quantifying how much of each metric is packed into a film. It is about gauging how well these metrics are used. So maybe you could give Schindler’s List “N/A” in the humor metric and some other largely humorless movie a 2⁄10 based on the fact that you felt the other movie needed humor and didn’t have much. In that way, it seems all metrics not stated as N/A would have value and you would just need to figure out how to weight them. For instance:
A 9 9 9 9 wouldn’t necessarily score a better total than a 9 9 9 N/A...but it might, if the last category was weighted higher than one/some of the others.
I tried visualizing but I don’t know how that helps me construct a formula. I would imagine, in your example, the landscape would be mountainous. One movie may have both great suspense and great humor and be a great movie...another may have both great suspense and great humor and be just an okay movie. But then perhaps there is a movie with very low amounts of humor or suspense that is still a good movie for other reasons. So in that case neither of these metrics would be good predictors for that movie.
That’s kind of the core of the issue, as your exercise illustrates. Since in any given case, and metric can be a complete non-predictor of the outcome, I don’t know any way to construct the formula. It seems like you’d have to find some way to both include and exclude metrics based on (something).
So maybe the answer is the N/A thing I considered. Valuing movie metrics is not about quantifying how much of each metric is packed into a film. It is about gauging how well these metrics are used. So maybe you could give Schindler’s List “N/A” in the humor metric and some other largely humorless movie a 2⁄10 based on the fact that you felt the other movie needed humor and didn’t have much. In that way, it seems all metrics not stated as N/A would have value and you would just need to figure out how to weight them. For instance:
A 9 9 9 9 wouldn’t necessarily score a better total than a 9 9 9 N/A...but it might, if the last category was weighted higher than one/some of the others.