We need to optimize something (product, drug, prototype etc) by testing it on users.
Let's say we have a 6 factor 3 level full factorial experimental design. So we have 3x3x3x3x3x3 = 729 variations.
In addition, I think machine learning algorithms such as random forests can help.
Any thoughts on how to implement that from methodological point of view?