Examples of VectorWritable

de.jungblut.clustering.model.VectorWritable
Writable and comparable wrapper for dense vectors.
@author thomas.jungblut @deprecated use de.jungblut.writable.VectorWritable instead, but it is notcompatible to this class here.
de.jungblut.writable.VectorWritable
New and updated VectorWritable class that has all the other fancy combinations of vectors that are possible in my math library.
This class is not compatible to the one in the clustering package that has a totally different byte alignment in binary files. @author thomas.jungblut
org.apache.hama.commons.io.VectorWritable
Writable for dense vectors.
org.apache.hama.ml.writable.VectorWritable
Writable for dense vectors.
org.apache.mahout.math.VectorWritable

Examples of org.apache.mahout.math.VectorWritable

        + "] sd=" + sd);
    for (int i = 0; i < num; i++) {
      DenseVector v = new DenseVector(card);
      for (int j = 0; j < card; j++)
        v.set(j, UncommonDistributions.rNorm(mx, sd));
      sampleData.add(new VectorWritable(v));
    }
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(40, 1, 1, 3);
    generateSamples(30, 1, 0, 0.1);
    generateSamples(30, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new NormalModelDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 2);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(40, 1, 1, 3);
    generateSamples(30, 1, 0, 0.1);
    generateSamples(30, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new SampledNormalDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 2);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(40, 1, 1, 3);
    generateSamples(30, 1, 0, 0.1);
    generateSamples(30, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new AsymmetricSampledNormalDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 2);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(400, 1, 1, 3);
    generateSamples(300, 1, 0, 0.1);
    generateSamples(300, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new NormalModelDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 20);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(400, 1, 1, 3);
    generateSamples(300, 1, 0, 0.1);
    generateSamples(300, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new SampledNormalDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 20);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(400, 1, 1, 3);
    generateSamples(300, 1, 0, 0.1);
    generateSamples(300, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new AsymmetricSampledNormalDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 20);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(4000, 1, 1, 3);
    generateSamples(3000, 1, 0, 0.1);
    generateSamples(3000, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new NormalModelDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 200);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(4000, 1, 1, 3);
    generateSamples(3000, 1, 0, 0.1);
    generateSamples(3000, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new AsymmetricSampledNormalDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 200);
    assertNotNull(result);
  }

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Examples of org.apache.mahout.math.VectorWritable

    generateSamples(4000, 1, 1, 3);
    generateSamples(3000, 1, 0, 0.1);
    generateSamples(3000, 0, 1, 0.1);


    DirichletClusterer<VectorWritable> dc = new DirichletClusterer<VectorWritable>(
        sampleData, new SampledNormalDistribution(new VectorWritable(
            new DenseVector(2))), 1.0, 10, 1, 0);
    List<Model<VectorWritable>[]> result = dc.cluster(30);
    printResults(result, 200);
    assertNotNull(result);
  }

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