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https://issues.apache.org/jira/browse/OPENNLP-154?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13045114#comment-13045114
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Jason Baldridge commented on OPENNLP-154:
-----------------------------------------
I guess that was my Scala coming through, e.g. where I would have done the
loops:
for (int oid = 0; oid < numOutcomes; oid++)
prior[oid] = Math.exp(prior[oid]/maxPrior);
double normal = 0.0;
for (int oid = 0; oid < numOutcomes; oid++)
normal += prior[oid];
for (int oid = 0; oid < numOutcomes; oid++)
prior[oid] /= normal;
As something along the lines of :
val priorExp = prior map (outcomePrior => Math.exp(outcomePrior/maxPrior))
val normal = priorExp sum
val priorNorm = priorExp map (_/normal)
Anyway, I've changed it to be one loop:
double normal = 0.0;
for (int oid = 0; oid < numOutcomes; oid++) {
prior[oid] = Math.exp(prior[oid]/maxPrior);
normal += prior[oid];
}
Jason
> normalization in perceptron
> ---------------------------
>
> Key: OPENNLP-154
> URL: https://issues.apache.org/jira/browse/OPENNLP-154
> Project: OpenNLP
> Issue Type: Bug
> Components: Maxent
> Affects Versions: maxent-3.0.1-incubating
> Reporter: Jason Baldridge
> Assignee: Jason Baldridge
> Priority: Minor
> Fix For: tools-1.5.2-incubating, maxent-3.0.2-incubating
>
> Original Estimate: 0h
> Remaining Estimate: 0h
>
> I found some issues with the way perceptron output was normalized. It was
> sort of a strange way to handle negative numbers that didn't really work.
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