On 9/28/2011 12:20 PM, Jörn Kottmann wrote: > On 9/28/11 5:24 PM, [email protected] wrote: >> Hi, >> >> I am testing the Chunker, but I'm failing to get the same results as in >> 1.5.1. >> >> 1.5.1: >> >> Precision: 0.9255923572240226 >> Recall: 0.9220610430991112 >> F-Measure: 0.9238233255623465 >> >> 1.5.2: >> >> Precision: 0.9257575757575758 >> Recall: 0.9221868187154117 >> F-Measure: 0.9239687473746113 >> >> >> Maybe it is related to this >> https://issues.apache.org/jira/browse/OPENNLP-242 >> >> Or to this related to this: >> >> The results of the tagging performance may differ compared to the 1.5.1 >> release, since a bug was corrected in the event filtering. >> >> What should we do? >> >> > > I guess it is related to OPENNLP-242, I couldn't find the jira for the > second one, > but as far as I know it only affects the perceptron. Does anyone > remember what this > is about? > > Could you undo OPENNLP-242 and see if the result is identical again? > You could also > test the model from 1.5.2 with 1.5.1 to see if it was trained different. > > Anyway I doesn't look like we have a regression here. > > Jörn Jorn,
I was going based on memory... I don't know it may have been 1.5.1 that fixed that bug. The training works the same as 1.5.1 but, I also get different results with the 1.5.2 series for the outcomes. I couldn't find any reason, other than form my strange memory that remembers a fix that someone did that changed the counts for the events. I couldn't find anything else that would be effecting the outcomes for the evaluations. James
