Examples of org.apache.mahout.math.SparseMatrix

  }


  @Override
  public Matrix like() {
    if (chks[0].isSparse()) {
      return new SparseMatrix(rowSize(), columnSize());
    } else {
      return new DenseMatrix(rowSize(), columnSize());
    }
  }

    }


    Preconditions.checkNotNull(scoresPerFeature);
    Preconditions.checkNotNull(scoresPerLabel);


    Matrix scoresPerLabelAndFeature = new SparseMatrix(scoresPerLabel.size(), scoresPerFeature.size());
    for (Pair<IntWritable,VectorWritable> entry : new SequenceFileDirIterable<IntWritable,VectorWritable>(
        new Path(base, TrainNaiveBayesJob.SUMMED_OBSERVATIONS), PathType.LIST, PathFilters.partFilter(), conf)) {
      scoresPerLabelAndFeature.assignRow(entry.getFirst().get(), entry.getSecond().get());
    }
    
    // perLabelThetaNormalizer is only used by the complementary model, we do not instantiate it for the standard model
    Vector perLabelThetaNormalizer = null;
    if (isComplementary) {

Related Classes of org.apache.mahout.math.SparseMatrix

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