How to pick the best gear


#1

In this article, I take a look at 3 different methods for finding your best gear:

  • Best in bags
  • Sim every combination (batch simulation)
  • Hand pick some gear combos to sim (batch simulation)

#2

Hi Cat. Grats on the tool and the approach. Love to see this kind of innovations in this space. But (you know there was a ‘but’ coming, didn’t you), as I understand ‘Best in Bags’ relies on the computed ‘Stat Weights’. Now, the problem I have with this is that ‘stat weights’, while being accurate in at a very small distance form the current gear point, in many cases do not predict very well the outcomes when extrapolated to distances typical of even replacing one item such as a ring or neck (I main Fire Mage, so this might be class specific). I guess the same reasoning behind AMR’s ML approach applies here as well. The ‘fitness landscape’ is rugged, so extrapolating from a local gradient might with significant probability land you somewhere far from optimal, and even worse than where you started from. Could utulizing data from ML be a way to go to improve ‘Best in Bags’?


#3

Best in Bags uses the machine learning data, not stat weights, and we’re also rolling out “version 3” over this week and next that uses a much larger data set that can adapt to your talents, choose legendaries more reliably, etc.


#4

Thx for the clarifications, I misread the article then.


#5

The article is a little bit out of date. The new Machine Learning Data is vastly superior (at least in terms of technique, if not outcome).
The practical how to use remains the same.