There are a few others as well. >From the code, there are these:
public void setInterval(int interval) public void setInterval(int minInterval, int maxInterval) public void setPoolSize(int poolSize) public void setThreadCount(int threadCount) public void setAucEvaluator(OnlineAuc auc) private void setupOptimizer(int poolSize) public void setBest(State<Wrapper, CrossFoldLearner> best) public void setRecord(int record) public void setBuffer(List<TrainingExample> buffer) public void setEp(EvolutionaryProcess<Wrapper, CrossFoldLearner> ep) public void setSeed(State<Wrapper, CrossFoldLearner> seed) public void setAveragingWindow(int averagingWindow) public void setFreezeSurvivors(boolean freezeSurvivors) Aside from the ones you mention and the setAucEvaluator, most of these should not be used. There are also a number of other indirect knobs available if you access, for instance, the underlying evolutionary algorithm, or set options on the AUC evaluator or the prior. On Thu, May 19, 2011 at 10:23 PM, Xiaobo Gu <guxiaobo1...@gmail.com> wrote: > Hi Ted, > > Are interval, averagingWindow, thread count, and prior Fuction the > only four tuneable options of AdaptiveLogisticRegression? > > Regards, > > Xiaobo Gu > > > On Tue, May 10, 2011 at 11:26 PM, Ted Dunning <ted.dunn...@gmail.com> > wrote: > > In the meantime, look at building your own command line tool for > > AdaptiveLogisticRegression. > > > > On Tue, May 10, 2011 at 8:25 AM, Ted Dunning <ted.dunn...@gmail.com> > wrote: > > > >> Go for it. > >> > >> Produce a JIRA and a patch. > >> > >> > >> On Tue, May 10, 2011 at 8:19 AM, XiaoboGu <guxiaobo1...@gmail.com> > wrote: > >> > >>> Can you add a --algorithm option to the trainlogistic and runlogistic > >>> program, and other options need by specific algorithms, such as using > L1 or > >>> L2 prior, then TL and RL will be production ready tool for us. > >> > >> > >> > > >
