Sorry if this is a newbie question. How does one reinforce a predicted result as being favorable given the evaluation criteria of a problem to the CLA? For example if I was going to use the platform to predict which road I should drive on when conditions are icy outside, how does the platform know which route is the best? The trouble I am having is that it would seem that lots of people take lots of stupid routes when it is icy out and would therefore make for convoluted data. My understanding is that all the bad routes would just reinforce bad predictions from the CLA if I fed it through. Just because lots of people take a certain route, doesn't mean it is the best route. In the same way, just because McDonalds has served billions of hamburgers doesn't mean they are the best hamburgers (or even the best food). How do you apply a value judgment on top of a prediction?
Thanks, Benjamin
_______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
