It's cool that you got it working in time for the demo, but I think your reasoning is unsound. >I remembered this from my engineering days at the College of En

It's cool that you got it working in time for the demo, but I think your reasoning is unsound. >I remembered this from my engineering days at the College of Engineering, Trivandrum. It’s called the Normal Distribution, or Gaussian distribution. It’s based on the idea that data near the mean (the average) is more frequent than data far from the mean. There are a lot of non-normal distributions where that's the case. The normal distribution is a specific thing that arises from summing together lots of small random variables. It's not a good model of people moving sliders on a UI: a person's decision to set the value to e.g. 0.8 is really one discrete thing, not a sum of a bunch of independent micro-decisions. There's no physical/statistical law preventing someone from grabbing the slider and thrusting all the way to the left or the right, and in fact people do this all the time on UIs. The client can move the slider however he pleases ... So I think you just got lucky that the client didn't do that. Don't rely on it not happening in the future! (You could also imagine fitting a normal distribution to user behaviour, but it turns out the standard deviation is just really large. That would be technically defensible but also useless for your situation, since there would be substantial probability at the min/max values of the finite range. It would be close to uniform.) (Also, who's to say the mean is in the middle of the slider range?) Anyway I'm curious what the ML model was doing that took 15 seconds. Are you sure there's no way to speed it up?