On 9/28/2011 1:59 PM, [email protected] wrote: > On Wed, Sep 28, 2011 at 1:20 PM, Jörn Kottmann <[email protected]> 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<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. >> > I undone OPENNLP-242 and got the same result we had in 1.5.1. So it is the > issue 242 indeed. > > >> Anyway I doesn't look like we have a regression here. >> >> Jörn >> > Thanks, > William > William,
The training looks like it may be identical. Could there be something in the changes you did of the evaluator that may be causing the differences? I'm also getting different results for the namefinder and the output. The training output is identical to the 1.5.1 series. But, the F-measure, Recall, and Precision are different. James
