List of nonZeroes() Examples

Examples of nonZeroes()

Examples of org.apache.mahout.math.Vector.nonZeroes()

      Vector rowVector = similarity.normalize(sampledRowVector);


      int numNonZeroEntries = 0;
      double maxValue = Double.MIN_VALUE;


      for (Vector.Element element : rowVector.nonZeroes()) {
        RandomAccessSparseVector partialColumnVector = new RandomAccessSparseVector(Integer.MAX_VALUE);
        partialColumnVector.setQuick(row.get(), element.get());
        ctx.write(new IntWritable(element.index()), new VectorWritable(partialColumnVector));


        numNonZeroEntries++;

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Examples of org.apache.mahout.math.Vector.nonZeroes()

      throws IOException, InterruptedException {
      Iterator<VectorWritable> partialDotsIterator = partialDots.iterator();
      Vector dots = partialDotsIterator.next().get();
      while (partialDotsIterator.hasNext()) {
        Vector toAdd = partialDotsIterator.next().get();
        for (Element nonZeroElement : toAdd.nonZeroes()) {
          dots.setQuick(nonZeroElement.index(), dots.getQuick(nonZeroElement.index()) + nonZeroElement.get());
        }
      }


      Vector similarities = dots.like();

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Examples of org.apache.mahout.math.Vector.nonZeroes()

  public static Vector solveExplicit(VectorWritable ratingsWritable, OpenIntObjectHashMap<Vector> uOrM,
    double lambda, int numFeatures) {
    Vector ratings = ratingsWritable.get();


    List<Vector> featureVectors = Lists.newArrayListWithCapacity(ratings.getNumNondefaultElements());
    for (Vector.Element e : ratings.nonZeroes()) {
      int index = e.index();
      featureVectors.add(uOrM.get(index));
    }


    return AlternatingLeastSquaresSolver.solve(featureVectors, ratings, lambda, numFeatures);

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Examples of org.apache.mahout.math.Vector.nonZeroes()

  @Override
  protected void map(WritableComparable<?> key, VectorWritable value, Context context) throws IOException,
      InterruptedException {
    Vector probabilities = classifier.classify(value.get());
    Vector selections = policy.select(probabilities);
    for (Element el : selections.nonZeroes()) {
      classifier.train(el.index(), value.get(), el.get());
    }
  }


  @Override

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Examples of org.apache.mahout.math.Vector.nonZeroes()

        // classification yields probabilities
        Vector probabilities = classifier.classify(vector);
        // policy selects weights for models given those probabilities
        Vector weights = policy.select(probabilities);
        // training causes all models to observe data
        for (Vector.Element e : weights.nonZeroes()) {
          int index = e.index();
          classifier.train(index, vector, weights.get(index));
        }
      }
      // compute the posterior models

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Examples of org.apache.mahout.math.Vector.nonZeroes()

        // classification yields probabilities
        Vector probabilities = classifier.classify(vector);
        // policy selects weights for models given those probabilities
        Vector weights = classifier.getPolicy().select(probabilities);
        // training causes all models to observe data
        for (Vector.Element e : weights.nonZeroes()) {
          int index = e.index();
          classifier.train(index, vector, weights.get(index));
        }
      }
      // compute the posterior models

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Examples of org.apache.mahout.math.Vector.nonZeroes()

    Vector provider = v.isSequentialAccess() ? v : new SequentialAccessSparseVector(v);


    List<Object> terms = Lists.newLinkedList();
    String term = "";


    for (Element elem : provider.nonZeroes()) {


      if (hasBindings && bindings.length >= elem.index() + 1 && bindings[elem.index()] != null) {
        term = bindings[elem.index()];
      } else if (hasBindings || isSparse) {
        term = String.valueOf(elem.index());

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Examples of org.apache.mahout.math.Vector.nonZeroes()


    for (PrefAndSimilarityColumnWritable prefAndSimilarityColumn : values) {
      Vector simColumn = prefAndSimilarityColumn.getSimilarityColumn();
      float prefValue = prefAndSimilarityColumn.getPrefValue();
      /* count the number of items used for each prediction */
      for (Element e : simColumn.nonZeroes()) {
        int itemIDIndex = e.index();
        numberOfSimilarItemsUsed.setQuick(itemIDIndex, numberOfSimilarItemsUsed.getQuick(itemIDIndex) + 1);
      }


      if (denominators == null) {

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Examples of org.apache.mahout.math.Vector.nonZeroes()

      boolean firstIsOutFrag =  ((VectorWritable)v.get(0)).get().size() == outCardinality;
      Vector outFrag = firstIsOutFrag ? ((VectorWritable)v.get(0)).get() : ((VectorWritable)v.get(1)).get();
      Vector multiplier = firstIsOutFrag ? ((VectorWritable)v.get(1)).get() : ((VectorWritable)v.get(0)).get();


      VectorWritable outVector = new VectorWritable();
      for (Vector.Element e : multiplier.nonZeroes()) {
        row.set(e.index());
        outVector.set(outFrag.times(e.get()));
        out.collect(row, outVector);
      }
    }

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Examples of org.apache.mahout.math.Vector.nonZeroes()

    if (usersToRecommendFor != null && !usersToRecommendFor.contains(userID)) {
      return;
    }
    Vector userVector = maybePruneUserVector(value.get());


    for (Element e : userVector.nonZeroes()) {
      itemIndexWritable.set(e.index());
      vectorOrPref.set(userID, (float) e.get());
      context.write(itemIndexWritable, vectorOrPref);
    }
  }

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