本文整理汇总了Java中cc.mallet.types.RankedFeatureVector类的典型用法代码示例。如果您正苦于以下问题:Java RankedFeatureVector类的具体用法?Java RankedFeatureVector怎么用?Java RankedFeatureVector使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
RankedFeatureVector类属于cc.mallet.types包,在下文中一共展示了RankedFeatureVector类的11个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Java代码示例。
示例1: countFeatures
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
private static RankedFeatureVector countFeatures(InstanceList ilist, boolean countInstances) {
int numFeatures = ilist.getDataAlphabet().size();
double[] counts = new double[numFeatures];
for (int i = 0; i < ilist.size(); i++) {
Instance inst = ilist.get(i);
if (ilist.getInstanceWeight(i) == 0) {
continue;
}
Object data = inst.getData();
if (data instanceof FeatureVectorSequence) {
FeatureVectorSequence fvs = (FeatureVectorSequence) data;
for (int j = 0; j < fvs.size(); j++) {
countVector(counts, fvs.get(j), countInstances);
}
} else {
throw new IllegalArgumentException("Currently only handles FeatureVectorSequence data");
}
}
return new RankedFeatureVector(ilist.getDataAlphabet(), counts);
}
开发者ID:steveash,项目名称:jg2p,代码行数:21,代码来源:FeatureSelections.java
示例2: testBiNormalSeparation
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public void testBiNormalSeparation() {
BinaryTestData binaryTestData = new BinaryTestData(4);
binaryTestData.addInstance(new int[] {0, 1}, true);
binaryTestData.addInstance(new int[] {0, 2}, true);
binaryTestData.addInstance(new int[] {2, 3}, false);
binaryTestData.addInstance(new int[] {3}, false);
InstanceList iList = binaryTestData.getInstanceList();
RankedFeatureVector rankedFeatureVector = new BiNormalSeparation.Factory()
.newRankedFeatureVector(iList);
assertEquals(6.58, rankedFeatureVector.getValueAtRank(0), 0.005);
assertEquals(3.29, rankedFeatureVector.getValueAtRank(2), 0.005);
assertEquals(0, rankedFeatureVector.getValueAtRank(3), 0);
assertEquals(6.58, rankedFeatureVector.getValueAtRank(1), 0.005);
assertEquals(2, rankedFeatureVector.getIndexAtRank(3));
assertEquals(1, rankedFeatureVector.getIndexAtRank(2));
}
开发者ID:mimno,项目名称:Mallet,代码行数:17,代码来源:TestBiNormalSeparation.java
示例3: gradientGainFrom
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
/**
* Returns a ranked feature vector of the gradient gain for the given training data on the given trained CRF. The
* instance list must have the target labels as LabelSequence
*/
public static RankedFeatureVector gradientGainFrom(InstanceList ilist, CRF crf) {
int numFeatures = ilist.getDataAlphabet().size();
double[] gradientgains = new double[numFeatures];
fillResults(ilist, crf, gradientgains, null, null);
return new RankedFeatureVector(ilist.getDataAlphabet(), gradientgains);
}
开发者ID:steveash,项目名称:jg2p,代码行数:11,代码来源:FeatureSelections.java
示例4: gradientGainRatioFrom
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public static RankedFeatureVector gradientGainRatioFrom(InstanceList ilist, CRF crf) {
int numFeatures = ilist.getDataAlphabet().size();
double[] gradientgains = new double[numFeatures];
double[] gradientlosses = new double[numFeatures];
fillResults(ilist, crf, null, gradientgains, gradientlosses);
return makeRatioVector(ilist, numFeatures, gradientgains, gradientlosses);
}
开发者ID:steveash,项目名称:jg2p,代码行数:9,代码来源:FeatureSelections.java
示例5: gradientsFrom
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public static Pair<RankedFeatureVector, RankedFeatureVector> gradientsFrom(InstanceList ilist, CRF crf) {
int numFeatures = ilist.getDataAlphabet().size();
double[] gradientgains = new double[numFeatures];
double[] pos = new double[numFeatures];
double[] neg = new double[numFeatures];
fillResults(ilist, crf, gradientgains, pos, neg);
return Pair.of(new RankedFeatureVector(ilist.getDataAlphabet(), gradientgains),
makeRatioVector(ilist, numFeatures, pos, neg));
}
开发者ID:steveash,项目名称:jg2p,代码行数:10,代码来源:FeatureSelections.java
示例6: makeRatioVector
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
private static RankedFeatureVector makeRatioVector(InstanceList ilist, int numFeatures,
double[] gradientgains,
double[] gradientlosses) {
double[] ratios = new double[numFeatures];
for (int i = 0; i < numFeatures; i++) {
double pos = gradientgains[i];
double neg = gradientlosses[i];
ratios[i] = (pos + 1.0) / (neg + 1.0);
}
return new RankedFeatureVector(ilist.getDataAlphabet(), ratios);
}
开发者ID:steveash,项目名称:jg2p,代码行数:12,代码来源:FeatureSelections.java
示例7: writeRankedToFile
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public static void writeRankedToFile(RankedFeatureVector rfv, File outputFile) {
try {
try (PrintWriter writer = new PrintWriter(Files.newWriter(outputFile, Charsets.UTF_8))) {
for (int i = 0; i < rfv.singleSize(); i++) {
Object objectAtRank = rfv.getObjectAtRank(i);
double gradAtRank = rfv.getValueAtRank(i);
writer.println(String.format("%s,%.5f", objectAtRank.toString(), gradAtRank));
}
}
} catch (IOException e) {
throw Throwables.propagate(e);
}
}
开发者ID:steveash,项目名称:jg2p,代码行数:15,代码来源:FeatureSelections.java
示例8: testSetRankOrder
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public void testSetRankOrder ()
{
Alphabet v = new Alphabet ();
RankedFeatureVector rfv =
new RankedFeatureVector (v, new int[] {v.lookupIndex ("a"), v.lookupIndex ("b"), v.lookupIndex ("c"), v.lookupIndex ("d") },
new double[] {3.0, 1.0, 2.0, 6.0});
System.out.println ("vector size ="+rfv.numLocations());
for (int i = 0; i < rfv.numLocations(); i++)
System.out.println ("Rank="+i+" value="+rfv.getValueAtRank(i));
}
开发者ID:mimno,项目名称:Mallet,代码行数:11,代码来源:TestRankedFeatureVector.java
示例9: print
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public void print (PrintWriter out)
{
out.println ("*** CRF STATES ***");
for (int i = 0; i < numStates (); i++) {
State s = (State) getState (i);
out.print ("STATE NAME=\"");
out.print (s.name); out.print ("\" ("); out.print (s.destinations.length); out.print (" outgoing transitions)\n");
out.print (" "); out.print ("initialWeight = "); out.print (parameters.initialWeights[i]); out.print ('\n');
out.print (" "); out.print ("finalWeight = "); out.print (parameters.finalWeights[i]); out.print ('\n');
out.println (" transitions:");
for (int j = 0; j < s.destinations.length; j++) {
out.print (" "); out.print (s.name); out.print (" -> "); out.println (s.getDestinationState (j).getName ());
for (int k = 0; k < s.weightsIndices[j].length; k++) {
out.print (" WEIGHTS = \"");
int widx = s.weightsIndices[j][k];
out.print (parameters.weightAlphabet.lookupObject (widx).toString ());
out.print ("\"\n");
}
}
out.println ();
}
if (parameters.weights == null)
out.println ("\n\n*** NO WEIGHTS ***");
else {
out.println ("\n\n*** CRF WEIGHTS ***");
for (int widx = 0; widx < parameters.weights.length; widx++) {
out.println ("WEIGHTS NAME = " + parameters.weightAlphabet.lookupObject (widx));
out.print (": <DEFAULT_FEATURE> = "); out.print (parameters.defaultWeights[widx]); out.print ('\n');
SparseVector transitionWeights = parameters.weights[widx];
if (transitionWeights.numLocations () == 0)
continue;
RankedFeatureVector rfv = new RankedFeatureVector (inputAlphabet, transitionWeights);
for (int m = 0; m < rfv.numLocations (); m++) {
double v = rfv.getValueAtRank (m);
//int index = rfv.indexAtLocation (rfv.getIndexAtRank (m)); // This doesn't make any sense. How did this ever work? -akm 12/2007
int index = rfv.getIndexAtRank (m);
Object feature = inputAlphabet.lookupObject (index);
if (v != 0) {
out.print (": "); out.print (feature); out.print (" = "); out.println (v);
}
}
}
}
out.flush ();
}
开发者ID:kostagiolasn,项目名称:NucleosomePatternClassifier,代码行数:48,代码来源:CRF.java
示例10: featureCountsFrom
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public static RankedFeatureVector featureCountsFrom(InstanceList ilist) {
return countFeatures(ilist, true);
}
开发者ID:steveash,项目名称:jg2p,代码行数:4,代码来源:FeatureSelections.java
示例11: featureSumFrom
import cc.mallet.types.RankedFeatureVector; //导入依赖的package包/类
public static RankedFeatureVector featureSumFrom(InstanceList ilist) {
return countFeatures(ilist, false);
}
开发者ID:steveash,项目名称:jg2p,代码行数:4,代码来源:FeatureSelections.java
注:本文中的cc.mallet.types.RankedFeatureVector类示例整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。 |
请发表评论