Package org.apache.mahout.math.neighborhood

Examples of org.apache.mahout.math.neighborhood.ProjectionSearch.addAll()

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   */
  public static List<OnlineSummarizer> summarizeClusterDistances(Iterable<? extends Vector> datapoints,
                                                                 Iterable<? extends Vector> centroids,
                                                                 DistanceMeasure distanceMeasure) {
    UpdatableSearcher searcher = new ProjectionSearch(distanceMeasure, 3, 1);
    searcher.addAll(centroids);
    List<OnlineSummarizer> summarizers = Lists.newArrayList();
    if (searcher.size() == 0) {
      return summarizers;
    }
    for (int i = 0; i < searcher.size(); ++i) {
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   * @return the total cost described above.
   */
  public static double totalClusterCost(Iterable<? extends Vector> datapoints, Iterable<? extends Vector> centroids) {
    DistanceMeasure distanceMeasure = new EuclideanDistanceMeasure();
    UpdatableSearcher searcher = new ProjectionSearch(distanceMeasure, 3, 1);
    searcher.addAll(centroids);
    return totalClusterCost(datapoints, searcher);
  }

  /**
   * Adds up the distances from each point to its closest cluster and returns the sum.
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   */
  public static List<OnlineSummarizer> summarizeClusterDistances(Iterable<? extends Vector> datapoints,
                                                                 Iterable<? extends Vector> centroids,
                                                                 DistanceMeasure distanceMeasure) {
    UpdatableSearcher searcher = new ProjectionSearch(distanceMeasure, 3, 1);
    searcher.addAll(centroids);
    List<OnlineSummarizer> summarizers = Lists.newArrayList();
    if (searcher.size() == 0) {
      return summarizers;
    }
    for (int i = 0; i < searcher.size(); ++i) {
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   * @return the total cost described above.
   */
  public static double totalClusterCost(Iterable<? extends Vector> datapoints, Iterable<? extends Vector> centroids) {
    DistanceMeasure distanceMeasure = new EuclideanDistanceMeasure();
    UpdatableSearcher searcher = new ProjectionSearch(distanceMeasure, 3, 1);
    searcher.addAll(centroids);
    return totalClusterCost(datapoints, searcher);
  }

  /**
   * Adds up the distances from each point to its closest cluster and returns the sum.
View Full Code Here
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   */
  public static List<OnlineSummarizer> summarizeClusterDistances(Iterable<? extends Vector> datapoints,
                                                                 Iterable<? extends Vector> centroids,
                                                                 DistanceMeasure distanceMeasure) {
    UpdatableSearcher searcher = new ProjectionSearch(distanceMeasure, 3, 1);
    searcher.addAll(centroids);
    List<OnlineSummarizer> summarizers = Lists.newArrayList();
    if (searcher.size() == 0) {
      return summarizers;
    }
    for (int i = 0; i < searcher.size(); ++i) {
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   * @return the total cost described above.
   */
  public static double totalClusterCost(Iterable<? extends Vector> datapoints, Iterable<? extends Vector> centroids) {
    DistanceMeasure distanceMeasure = new EuclideanDistanceMeasure();
    UpdatableSearcher searcher = new ProjectionSearch(distanceMeasure, 3, 1);
    searcher.addAll(centroids);
    return totalClusterCost(datapoints, searcher);
  }

  /**
   * Adds up the distances from each point to its closest cluster and returns the sum.
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