The documents about swarming illustrate how the error is calculated,but i cant understand what the error itself mean.That is on what comparisons does i get the error value?
What i understand is,if i have 100 data units then swarming would use may be some 50 data units and then predict 51 using different models and it choose the model which is close to the prediction of 51(the error calculation model prediction subtracted by 51). Finally the best model swarming has given is used to predict unknown data i.e 101 or 102 or so on... Is this view correct?
