In AAE we have predicted value and true value.We already have the true value but how we get the predicted value.
On 16 January 2015 at 19:17, Scott Purdy <[email protected]> wrote: > The error metrics are configurable. The two most commonly used are average > absolute error (AAE) and mean absolute percentage error (MAPE). You can > also specify a moving window so instead of calculating the error at a given > point over all data so far, you calculate the metric over the last 1000 > records (or whatever you specify). > > Swarming doesn't change the model it uses on a per-record basis. Instead, > when it picks a new parameter set it runs it all the way through and then > takes the final error metric (which may be computed over just the last X > records) and compares it to other models tried. > > On Thu, Jan 15, 2015 at 7:36 PM, Dinesh Deshmukh <[email protected]> > wrote: > >> 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? >> >> >
