Examples of org.apache.mahout.math.Centroid.update()

org.apache.mahout.math.Centroid.update()

    Preconditions.checkArgument(datapoints.size() > 1, "Must have at least two datapoints points to cluster " +
        "sensibly");
    // Compute the centroid of all of the datapoints.  This is then used to compute the squared radius of the datapoints.
    Centroid center = new Centroid(datapoints.iterator().next());
    for (WeightedVector row : Iterables.skip(datapoints, 1)) {
      center.update(row);
    }
    // Given the centroid, we can compute \Delta_1^2(X), the total squared distance for the datapoints
    // this accelerates seed selection.
    double radius = 0;
    DistanceMeasure l2 = new SquaredEuclideanDistanceMeasure();

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    Preconditions.checkArgument(datapoints.size() >= numClusters,
        String.format("Must have more datapoints [%d] than clusters [%d]", datapoints.size(), numClusters));
    // Compute the centroid of all of the datapoints.  This is then used to compute the squared radius of the datapoints.
    Centroid center = new Centroid(datapoints.iterator().next());
    for (WeightedVector row : Iterables.skip(datapoints, 1)) {
      center.update(row);
    }


    // Given the centroid, we can compute \Delta_1^2(X), the total squared distance for the datapoints
    // this accelerates seed selection.
    double deltaX = 0;

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        // We will update the centroid by removing it from the searcher and reinserting it to
        // ensure consistency.
        if (!centroids.remove(centroid, Constants.EPSILON)) {
          throw new RuntimeException("Unable to remove centroid");
        }
        centroid.update(row);
        centroids.add(centroid);


      }
      ++numProcessedDatapoints;

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