That sounds like a continuous optimization problem. Look at the org.apache.mahout.ep.EvolutionaryProcess
It is an implementation of recorded step meta-mutation and does quite well on many problems. See http://arxiv.org/abs/0803.3838 for details on the algorithm. On Sat, Aug 11, 2012 at 8:24 PM, Jason Thomas <[email protected]>wrote: > It's a search/optimization problem. I have an existing complex model > (multiple neural nets) and I need to find the right combination of inputs > to achieve certain target outputs. It seems like GA would be the easiest > approach for this. > > I'll take a look at the old Watchmaker code and maybe try to improve on it. > Thanks for the help. > > -Jason > > > On Sat, Aug 11, 2012 at 6:20 PM, Ted Dunning <[email protected]> > wrote: > > > The Watchmaker implementation was not very scalable and there was no > > perceptible user demand for it. There was also nobody who was > maintaining > > it. > > > > So we nuked it. > > > > There is still a limited evolutionary algorithm that is part of the > > AdaptiveLogisticRegression. It is likely to be pretty good on problems > > that involve the optimization of functions of continuous variables. > > > > What sort of GA do you need? > > > > On Sat, Aug 11, 2012 at 6:37 AM, Jason Thomas <[email protected] > > >wrote: > > > > > I noticed Watchmaker support was removed. Could someone tell me if > this > > > was because genetic algorithms in general aren't in line with Mahout > > goals > > > or was there a problem specifically with the Watchmaker > > > integration/implementation? I need scalable GA and I'm trying to > figure > > > out how to proceed. > > > > > > Thanks, > > > Jason > > > > > >
