Package org.apache.mahout.clustering.fuzzykmeans

Examples of org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer


      for (Model<VectorWritable> model : models) {
        SoftCluster sc = (SoftCluster) model;
        clusters.add(sc);
        distances.add(sc.getMeasure().distance(instance, sc.getCenter()));
      }
      return new FuzzyKMeansClusterer().computePi(clusters, distances);
    } else {
      int i = 0;
      for (Model<VectorWritable> model : models) {
        pdfs.set(i++, model.pdf(new VectorWritable(instance)));
      }
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      for (Cluster model : models) {
        SoftCluster sc = (SoftCluster) model;
        clusters.add(sc);
        distances.add(sc.getMeasure().distance(instance, sc.getCenter()));
      }
      return new FuzzyKMeansClusterer().computePi(clusters, distances);
    } else {
      int i = 0;
      Vector pdfs = new DenseVector(models.size());
      for (Cluster model : models) {
        pdfs.set(i++, model.pdf(new VectorWritable(instance)));
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    for (Cluster model : prior.getModels()) {
      SoftCluster sc = (SoftCluster) model;
      clusters.add(sc);
      distances.add(sc.getMeasure().distance(data, sc.getCenter()));
    }
    FuzzyKMeansClusterer fuzzyKMeansClusterer = new FuzzyKMeansClusterer();
    fuzzyKMeansClusterer.setM(m);
    return fuzzyKMeansClusterer.computePi(clusters, distances);
  }
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      for (Cluster model : models) {
        SoftCluster sc = (SoftCluster) model;
        clusters.add(sc);
        distances.add(sc.getMeasure().distance(instance, sc.getCenter()));
      }
      return new FuzzyKMeansClusterer().computePi(clusters, distances);
    } else {
      int i = 0;
      for (Cluster model : models) {
        pdfs.set(i++, model.pdf(new VectorWritable(instance)));
      }
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    for (Cluster model : prior.getModels()) {
      SoftCluster sc = (SoftCluster) model;
      clusters.add(sc);
      distances.add(sc.getMeasure().distance(data, sc.getCenter()));
    }
    FuzzyKMeansClusterer fuzzyKMeansClusterer = new FuzzyKMeansClusterer();
    fuzzyKMeansClusterer.setM(m);
    return fuzzyKMeansClusterer.computePi(clusters, distances);
  }
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