Let's say we want to conclude that attributes
D are the most relevant attributes to maximize the precision of predicting
Y, and then rank those attributes based on their importance/relevance.
Now let's say SVM and Random Forest both seem to be good fits to model the data and Random Forest provides better performance (higher precision). Does that mean Random Forest would also be a better choice to rank the attributes according to their relevance to
In a more general sense, can we say the best algorithm for maximizing precision of predicting
Y is also the best algorithm to rank the relevance of attributes to