Actually, I measured the model effectiveness, not the memory x performance.
2013/10/7 Michael Schmitz <[email protected]> > Hi Jorn, let me be more precise. Do you have a notion of how the > precision-recall curve (AUC) changes as a function of the number of > annotations? I'm curious how many annotations are needed for a model > with reasonable precision-recall AUC and reasonable performance > (memory and speed). > > Peace. Michael > > On Mon, Oct 7, 2013 at 3:29 PM, Jörn Kottmann <[email protected]> wrote: > > On 10/07/2013 11:00 PM, Michael Schmitz wrote: > >> > >> Do you know how many sentences/tokens were annotated for the OpenNLP > >> POS and CHUNK models? Do you have an idea of the "sweet spot" for > >> number of annotations vs performance? > > > > > > If the model gets bigger the computations get more complex, but as far > as I > > know > > the effect of the model not fitting anymore in the CPU cache is much more > > significant then > > that. I am using hash based int features to reduce the memory footprint > in > > the name finder. > > > > I don't have much experience with the Chunker or Pos Tagger in regards to > > performance, but > > it should be easy to do a series of tests, the command line tools have > built > > in performance monitoring. > > > > Jörn >
