So basically I have a large set of features corresponding to a metric - like many ML problems.
What I want to know is: can we correlate the variance of metric with the variation in each feature.
I have features x, y, z that produce an output say 10. When I vary x, no matter how much I vary it, the output stays relatively close to 10. However, when I vary y the output is heavily influenced.
Is there a good technique to be able to assign a value correlating x and/or y to the metric?
I'm mostly looking for direction here.. i.e. techniques or relevant papers. In my experience I haven't really come across this problem. I don't have a good solution in my toolbelt.