Package org.apache.spark.mllib.linalg

Examples of org.apache.spark.mllib.linalg.Vector

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      Vectors.dense(1.0, 2.0, 6.0),
      Vectors.dense(1.0, 3.0, 0.0),
      Vectors.dense(1.0, 4.0, 6.0)
    );

    Vector expectedCenter = Vectors.dense(1.0, 3.0, 4.0);

    JavaRDD<Vector> data = sc.parallelize(points, 2);
    KMeansModel model = KMeans.train(data.rdd(), 1, 1, 1, KMeans.K_MEANS_PARALLEL());
    assertEquals(1, model.clusterCenters().length);
    assertEquals(expectedCenter, model.clusterCenters()[0]);
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      Vectors.dense(1.0, 2.0, 6.0),
      Vectors.dense(1.0, 3.0, 0.0),
      Vectors.dense(1.0, 4.0, 6.0)
    );

    Vector expectedCenter = Vectors.dense(1.0, 3.0, 4.0);

    JavaRDD<Vector> data = sc.parallelize(points, 2);
    KMeansModel model = new KMeans().setK(1).setMaxIterations(5).run(data.rdd());
    assertEquals(1, model.clusterCenters().length);
    assertEquals(expectedCenter, model.clusterCenters()[0]);
View Full Code Here
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      Vectors.dense(1.0, 2.0, 6.0),
      Vectors.dense(1.0, 3.0, 0.0),
      Vectors.dense(1.0, 4.0, 6.0)
    );

    Vector expectedCenter = Vectors.dense(1.0, 3.0, 4.0);

    JavaRDD<Vector> data = sc.parallelize(points, 2);
    KMeansModel model = KMeans.train(data.rdd(), 1, 1, 1, KMeans.K_MEANS_PARALLEL());
    assertEquals(1, model.clusterCenters().length);
    assertEquals(expectedCenter, model.clusterCenters()[0]);
View Full Code Here
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      Vectors.dense(1.0, 2.0, 6.0),
      Vectors.dense(1.0, 3.0, 0.0),
      Vectors.dense(1.0, 4.0, 6.0)
    );

    Vector expectedCenter = Vectors.dense(1.0, 3.0, 4.0);

    JavaRDD<Vector> data = sc.parallelize(points, 2);
    KMeansModel model = new KMeans().setK(1).setMaxIterations(5).run(data.rdd());
    assertEquals(1, model.clusterCenters().length);
    assertEquals(expectedCenter, model.clusterCenters()[0]);
View Full Code Here
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Related Classes of org.apache.spark.mllib.linalg.Vector

  • org.apache.spark.mllib.clustering.JavaKMeansSuite
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