本文整理了Java中edu.illinois.cs.cogcomp.lbjava.classify.Feature.toString()
方法的一些代码示例,展示了Feature.toString()
的具体用法。这些代码示例主要来源于Github
/Stackoverflow
/Maven
等平台,是从一些精选项目中提取出来的代码,具有较强的参考意义,能在一定程度帮忙到你。Feature.toString()
方法的具体详情如下:
包路径:edu.illinois.cs.cogcomp.lbjava.classify.Feature
类名称:Feature
方法名:toString
[英]Returns a string representation of this Feature
.
[中]返回此Feature
的字符串表示形式。
代码示例来源:origin: edu.illinois.cs.cogcomp/LBJava
/** Returns a text representation of this lexicon (for debugging). */
public String toString() {
StringBuffer result = new StringBuffer();
for (int i = 0; i < lexiconInv.size(); ++i) {
result.append(", ");
result.append(i);
result.append(": ");
result.append(lexiconInv.get(i).toString());
}
if (lexiconInv.size() > 0)
return result.substring(2);
return result.toString();
}
代码示例来源:origin: edu.illinois.cs.cogcomp/LBJava
data[i][1] = featureCounts.get(i);
rowLabels[i] =
p ? lexiconInv.get(i).toString() : lexiconInv.get(i).toStringNoPackage();
data[i][j + 1] = perClassFeatureCounts.get(j, i);
rowLabels[i] =
p ? lexiconInv.get(i).toString() : lexiconInv.get(i).toStringNoPackage();
data[i][0] = i;
rowLabels[i] =
p ? lexiconInv.get(i).toString() : lexiconInv.get(i).toStringNoPackage();
代码示例来源:origin: CogComp/cogcomp-nlp
FeatureVector fv2 = features2.classify(w);
for (int k = 0; k < fv1.size(); k++) {
String s = fv1.getFeature(k).toString();
out.print(" " + s.substring(s.indexOf(':') + 1, s.length()));
String s = fv2.getFeature(k).toString();
out.print(" " + s.substring(s.indexOf(':') + 1, s.length()));
代码示例来源:origin: edu.illinois.cs.cogcomp/illinois-ner
FeatureVector fv2 = features2.classify(w);
for (int k = 0; k < fv1.size(); k++) {
String s = fv1.getFeature(k).toString();
out.print(" " + s.substring(s.indexOf(':') + 1, s.length()));
String s = fv2.getFeature(k).toString();
out.print(" " + s.substring(s.indexOf(':') + 1, s.length()));
代码示例来源:origin: edu.illinois.cs.cogcomp/illinois-mlner
FeatureVector fv2 = features2.classify(w);
for (int k = 0; k < fv1.size(); k++) {
String s = fv1.getFeature(k).toString();
out.print(" " + s.substring(s.indexOf(':') + 1, s.length()));
String s = fv2.getFeature(k).toString();
out.print(" " + s.substring(s.indexOf(':') + 1, s.length()));
代码示例来源:origin: edu.illinois.cs.cogcomp/saul
if (!(att.name().equals(f.toString()))) {
System.err.println("WekaWrapper: Error - makeInstance encountered a misaligned "
+ "attribute-feature pair.");
System.err.println(" " + att.name() + " and " + f.toString()
+ " should have been identical.");
new Exception().printStackTrace();
代码示例来源:origin: edu.illinois.cs.cogcomp/illinois-comma
public CommaSequence(List<Comma> commas, Lexiconer lexicon, List<Classifier> lbjExtractors) {
Collections.sort(commas, new Comparator<Comma>() {
@Override
public int compare(Comma o1, Comma o2) {
return o1.getPosition() - o2.getPosition();
}
});
this.sortedCommas = commas;
baseFeatures = new IFeatureVector[sortedCommas.size()];
for (int i = 0; i < sortedCommas.size(); i++) {
FeatureVector lbjFeatureVector = new FeatureVector();
for (Classifier lbjExtractor : lbjExtractors)
lbjFeatureVector.addFeatures(lbjExtractor.classify(sortedCommas.get(i)));
FeatureVectorBuffer slFeatureVectorBuffer = new FeatureVectorBuffer();
for (int j = 0; j < lbjFeatureVector.featuresSize(); j++) {
String featureString = lbjFeatureVector.getFeature(j).toString();
if (lexicon.isAllowNewFeatures())
lexicon.addFeature(featureString);
if (lexicon.containFeature(featureString))
slFeatureVectorBuffer.addFeature(lexicon.getFeatureId(featureString), 1);
else
slFeatureVectorBuffer.addFeature(
lexicon.getFeatureId(CommaIOManager.unknownFeature), 1);
}
baseFeatures[i] = slFeatureVectorBuffer.toFeatureVector();
}
}
}
代码示例来源:origin: CogComp/cogcomp-nlp
public CommaSequence(List<Comma> commas, Lexiconer lexicon, List<Classifier> lbjExtractors) {
Collections.sort(commas, new Comparator<Comma>() {
@Override
public int compare(Comma o1, Comma o2) {
return o1.getPosition() - o2.getPosition();
}
});
this.sortedCommas = commas;
baseFeatures = new IFeatureVector[sortedCommas.size()];
for (int i = 0; i < sortedCommas.size(); i++) {
FeatureVector lbjFeatureVector = new FeatureVector();
for (Classifier lbjExtractor : lbjExtractors)
lbjFeatureVector.addFeatures(lbjExtractor.classify(sortedCommas.get(i)));
FeatureVectorBuffer slFeatureVectorBuffer = new FeatureVectorBuffer();
for (int j = 0; j < lbjFeatureVector.featuresSize(); j++) {
String featureString = lbjFeatureVector.getFeature(j).toString();
if (lexicon.isAllowNewFeatures())
lexicon.addFeature(featureString);
if (lexicon.containFeature(featureString))
slFeatureVectorBuffer.addFeature(lexicon.getFeatureId(featureString), 1);
else
slFeatureVectorBuffer.addFeature(
lexicon.getFeatureId(CommaIOManager.unknownFeature), 1);
}
baseFeatures[i] = slFeatureVectorBuffer.toFeatureVector();
}
}
}
代码示例来源:origin: edu.illinois.cs.cogcomp/saul
Feature f = lexicon.lookupKey(featureIndex);
Attribute a = f.isDiscrete() ?
new Attribute(f.toString(), binaryValues) :
new Attribute(f.toString());
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