Package org.uncommons.maths.random

Examples of org.uncommons.maths.random.MersenneTwisterRNG.nextDouble()

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    for (int nloop = 0; nloop < n; nloop++) {
      long datasetSize = 100;
      MersenneTwisterRNG rng = new MersenneTwisterRNG();
      byte[] seed = rng.getSeed();
      double threshold = rng.nextDouble();

      JobConf conf = new JobConf();
      RndLineRecordReader rndReader;
      Set<Long> dataset = new HashSet<Long>();
      LongWritable key = new LongWritable();
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    for (int nloop = 0; nloop < n; nloop++) {
      MersenneTwisterRNG rng = new MersenneTwisterRNG();

      byte[] seed = rng.getSeed();
      double threshold = rng.nextDouble();
      boolean training = rng.nextBoolean();

      DatasetSplit split = new DatasetSplit(seed, threshold);
      split.setTraining(training);
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    int n = 20;

    for (int nloop = 0; nloop < n; nloop++) {
      MersenneTwisterRNG rng = (MersenneTwisterRNG) RandomUtils.getRandom();
      byte[] seed = rng.getSeed();
      double threshold = rng.nextDouble();

      JobConf conf = new JobConf();
      Set<Long> dataset = new HashSet<Long>();
      LongWritable key = new LongWritable();
      Text value = new Text();
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    for (int nloop = 0; nloop < n; nloop++) {
      MersenneTwisterRNG rng = (MersenneTwisterRNG) RandomUtils.getRandom();

      byte[] seed = rng.getSeed();
      double threshold = rng.nextDouble();
      boolean training = rng.nextBoolean();

      DatasetSplit split = new DatasetSplit(seed, threshold);
      split.setTraining(training);
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