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MutableContext.setParameter
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How to use
setParameter
method
in
opennlp.model.MutableContext

Best Java code snippets using opennlp.model.MutableContext.setParameter (Showing top 14 results out of 315)

  • Common ways to obtain MutableContext
private void myMethod () {
MutableContext m =
  • Codota Iconnew MutableContext(outcomePattern, new double[numActiveOutcomes])
  • Smart code suggestions by Codota
}
origin: org.maochen.nlp/CoreNLP-NLP

modelExpect[pi].setParameter(aoi, 0.0); // re-initialize to 0.0's
origin: Ailab403/ailab-mltk4j

modelExpect[pi].setParameter(aoi, 0.0); // re-initialize to 0.0's
origin: org.apache.opennlp/opennlp-maxent

modelExpect[pi].setParameter(aoi, 0.0); // re-initialize to 0.0's
origin: joliciel-informatique/talismane

modelExpects[i][pi].setParameter(aoi, 0.0); // re-initialize to 0.0's
origin: org.maochen.nlp/CoreNLP-NLP

for (int aoi = 0; aoi < numActiveOutcomes; aoi++) {
  int oi = outcomePattern[aoi];
  params[pi].setParameter(aoi, 0.0);
  for (MutableContext[] modelExpect : modelExpects) {
    modelExpect[pi].setParameter(aoi, 0.0);
    observedExpects[pi].setParameter(aoi, featCount[pi][oi]);
  } else if (useSimpleSmoothing) {
    observedExpects[pi].setParameter(aoi, smoothingObservation);
origin: org.apache.opennlp/opennlp-maxent

averageParams[pi].setParameter(oi, predParams[oi]);
origin: Ailab403/ailab-mltk4j

averageParams[pi].setParameter(oi, predParams[oi]);
origin: org.apache.opennlp/opennlp-maxent

params[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
for (int aoi=0;aoi<numOutcomes;aoi++)
 params[pi].setParameter(aoi, 0.0);
 summedParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
 for (int aoi=0;aoi<numOutcomes;aoi++)
  summedParams[pi].setParameter(aoi, 0.0);
for (int pi = 0; pi < numPreds; pi++) 
 for (int aoi=0;aoi<numOutcomes;aoi++)
  summedParams[pi].setParameter(aoi, summedParams[pi].getParameters()[aoi]/numTimesSummed);
origin: Ailab403/ailab-mltk4j

params[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
for (int aoi=0;aoi<numOutcomes;aoi++)
 params[pi].setParameter(aoi, 0.0);
 summedParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
 for (int aoi=0;aoi<numOutcomes;aoi++)
  summedParams[pi].setParameter(aoi, 0.0);
for (int pi = 0; pi < numPreds; pi++) 
 for (int aoi=0;aoi<numOutcomes;aoi++)
  summedParams[pi].setParameter(aoi, summedParams[pi].getParameters()[aoi]/numTimesSummed);
origin: joliciel-informatique/talismane

for (int aoi = 0; aoi < numActiveOutcomes; aoi++) {
 int oi = outcomePattern[aoi];
 params[pi].setParameter(aoi, 0.0);
 for (int i = 0; i < modelExpects.length; i++)
  modelExpects[i][pi].setParameter(aoi, 0.0);
 if (predCount[pi][oi] > 0) {
  observedExpects[pi].setParameter(aoi, predCount[pi][oi]);
 } else if (useSimpleSmoothing) {
  observedExpects[pi].setParameter(aoi, smoothingObservation);
origin: org.apache.opennlp/opennlp-maxent

for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
 int oi = outcomePattern[aoi];
 params[pi].setParameter(aoi, 0.0);
 for (MutableContext[] modelExpect : modelExpects) {
  modelExpect[pi].setParameter(aoi, 0.0);
   observedExpects[pi].setParameter(aoi, predCount[pi][oi]);
  observedExpects[pi].setParameter(aoi,smoothingObservation);
origin: Ailab403/ailab-mltk4j

for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
 int oi = outcomePattern[aoi];
 params[pi].setParameter(aoi, 0.0);
 for (MutableContext[] modelExpect : modelExpects) {
  modelExpect[pi].setParameter(aoi, 0.0);
   observedExpects[pi].setParameter(aoi, predCount[pi][oi]);
  observedExpects[pi].setParameter(aoi,smoothingObservation);
origin: org.apache.opennlp/opennlp-maxent

if (useAverage) averageParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
for (int aoi=0;aoi<numOutcomes;aoi++) {
 params[pi].setParameter(aoi, 0.0);
 if (useAverage) averageParams[pi].setParameter(aoi, 0.0);
origin: Ailab403/ailab-mltk4j

if (useAverage) averageParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
for (int aoi=0;aoi<numOutcomes;aoi++) {
 params[pi].setParameter(aoi, 0.0);
 if (useAverage) averageParams[pi].setParameter(aoi, 0.0);
opennlp.modelMutableContextsetParameter

Javadoc

Assigns the parameter or expected value at the specified outcomeIndex the specified value.

Popular methods of MutableContext

  • <init>
    Creates a new parameters object with the specified parameters associated with the specified outcome
  • getOutcomes
  • getParameters
  • updateParameter
    Updated the parameter or expected value at the specified outcomeIndex by adding the specified value

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