Hi everyone, The documents you mentioned answered my 1st question(How error is calculated from models),but what does the error itself mean? 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). The best model swarming has given is used to predict unknown data i.e 101 or 102 or so on...
Is this view correct? On 5 January 2015 at 18:32, Matthew Taylor <[email protected]> wrote: > Have you seen the following documents? > > - https://github.com/numenta/nupic/wiki/Swarming-Algorithm > - https://github.com/numenta/nupic/wiki/Running-Swarms > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Sat, Jan 3, 2015 at 5:43 AM, Dinesh Deshmukh <[email protected]> > wrote: > > Reference https://www.youtube.com/watch?v=xYPKjKQ4YZ0 > > > > 1.How is the error calculated from the models. > > 2.In Particle Swarm Optimization what does local min and global min mean. > > > >
