I have following business domain. I have a product with three outputs/labels. The outputs are impacted by 1000 procedures, each procedure is digitized and measured. The customer wants to know what is the most influential procedures on the outputs.
1. From Pearson correlation coefficient we could learn how two variables' relationship, say 1 is proportional, -1 is negative proportional and 0 is no relation. So I could find the biggest value of Pearson correlation coefficient to find more influential procedures.
2. From Random Forest algorithm, I could know the top feature importance. So I could identify also the most influential procedures.
Which one is better?