List of rank() Examples

Examples of rank()

Jama.Matrix.rank()
Matrix rank @return effective numerical rank, obtained from SVD.
com.nr.la.SVD.rank()
Return the rank of A, after zeroing any singular values smaller than thresh. If thresh is negative, a default value based on estimated roundoff is used. @param thresh @return
com.nr.sort.Indexx.rank()
eu.stratosphere.test.iterative.nephele.danglingpagerank.PageRankStats.rank()
ivory.smrf.retrieval.MRFDocumentRanker.rank()
org.apache.flink.test.iterative.nephele.danglingpagerank.PageRankStats.rank()
org.eclipse.sisu.inject.DefaultRankingFunction.rank()
weka.core.matrix.SingularValueDecomposition.rank()
Effective numerical matrix rank @return Number of nonnegligible singular values.

Examples of ivory.smrf.retrieval.MRFDocumentRanker.rank()

          else{  
            // Retrieve documents using this MRF.
            MRFDocumentRanker ranker = new MRFDocumentRanker(mrf, mNumHits);


            if (mExpander != null) {
              results = ranker.rank();
            }


            // Perform pseudo-relevance feedback, if requested.
            if (mExpander != null) {
              // Get expanded MRF.

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Examples of ivory.smrf.retrieval.MRFDocumentRanker.rank()

              // Re-rank documents according to expanded MRF.
              ranker = new MRFDocumentRanker(expandedMRF, mNumHits);
            }
  
            // Rank the documents.
            results = ranker.rank();


            //cascadeCost = ranker.getCost();
            cascadeCost = -1; //todo: later
        
          }

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Examples of org.apache.flink.test.iterative.nephele.danglingpagerank.PageRankStats.rank()

      
      PageRankStats stats = (PageRankStats) getIterationRuntimeContext().getPreviousIterationAggregate(CustomCompensatableDotProductCoGroup.AGGREGATOR_NAME);


      uniformRank = 1d / (double) numVertices;
      double lostMassFactor = (numVertices - stats.numVertices()) / (double) numVertices;
      rescaleFactor = (1 - lostMassFactor) / stats.rank();
    }
  }


  @Override
  public void map(VertexWithRankAndDangling pageWithRank, Collector<VertexWithRankAndDangling> out) throws Exception {

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Examples of org.eclipse.sisu.inject.DefaultRankingFunction.rank()

    bind(RankingFunction.class).toInstance(new RankingFunction()
    {
      private final RankingFunction function = new DefaultRankingFunction(rank.incrementAndGet());


      public <T> int rank(Binding<T> binding) {
        return function.rank(binding);
      }


      public int maxRank() {
        return Integer.MAX_VALUE; // potential max rank could be as high as MAX_VALUE if @Priority is used
      }

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Examples of weka.core.matrix.SingularValueDecomposition.rank()

    m_u = trainSVD.getU(); // left singular vectors
    m_s = trainSVD.getS(); // singular values
    m_v = trainSVD.getV(); // right singular vectors
    
    // find actual rank to use
    int maxSingularValues = trainSVD.rank();
    for (int i = 0; i < m_s.getRowDimension(); i++) {
      m_sumSquaredSingularValues += m_s.get(i, i) * m_s.get(i, i);
    }
    if (maxSingularValues == 0) { // no nonzero singular values (shouldn't happen)
      // reset values from computation

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Examples of weka.core.matrix.SingularValueDecomposition.rank()

    m_u = trainSVD.getU(); // left singular vectors
    m_s = trainSVD.getS(); // singular values
    m_v = trainSVD.getV(); // right singular vectors
    
    // find actual rank to use
    int maxSingularValues = trainSVD.rank();
    for (int i = 0; i < m_s.getRowDimension(); i++) {
      m_sumSquaredSingularValues += m_s.get(i, i) * m_s.get(i, i);
    }
    if (maxSingularValues == 0) { // no nonzero singular values (shouldn't happen)
      // reset values from computation

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