If I run a Random Forest on a set of data and get an accuracy of let's say 85% and I want to produce better results, I could just increase the amount of decision trees I use. Lets say I Increase the amount of trees I use and now I get an accuracy of 94%. If theoretically I used an infinite amount of trees would I get a perfect accuracy of 1 or as we increase the amount of trees is there a limit to how accurate we can become as we converge to a certain accuracy (like 98.76%). Of course there are many different factors to this but I think there should be a limit "n amount of trees" to where adding more wouldn't increase our accuracy or increase it by such a small amount that it doesn't matter anymore.