Package gov.sandia.cognition.math

Examples of gov.sandia.cognition.math.MutableDouble

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         */
        Preconditions.checkState(stateSums.getDomainSize() <= hmm.getNumStates());
        for (int j = 0; j < hmm.getNumStates(); j++) {
          final double classError = forwardResults.get(i).getElement(j) - stateSums.getFraction(j);
          Preconditions.checkState(!Double.isNaN(classError));
          classErrorRates.get(j).accumulate(new MutableDouble(classError));
        }
      }
    }
   
    List<Double> errMeans = Lists.newArrayList();
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          new UnivariateGaussian.SufficientStatistic();
      final RingAccumulator<MutableDouble> countSummary = new RingAccumulator<MutableDouble>();

      for (final MvGaussianDPDistribution mixtureDist : currentMixtureDistribution.getDomain()) {
        rmseSuffStat.update(observation.minus(mixtureDist.getMean()).norm2());
        countSummary.accumulate(new MutableDouble(mixtureDist.getDistributionCount()));
      }
      System.out.println("posterior RMSE mean:" + rmseSuffStat.getMean());
      System.out.println("posterior component counts:" + countSummary.getMean());
    }
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Related Classes of gov.sandia.cognition.math.MutableDouble

  • plm.gaussian.GaussianArHpWfPlFilterTest
  • plm.hmm.categorical.CategoricalHMMPLFilterTest
  • plm.hmm.gaussian.GaussianArHpHmmFilterTest
  • plm.util.clustering.MvGaussianDPRunner
  • plm.util.gaussian.GaussianArHpEvaluator
  • plm.util.gaussian.GaussianArHpRunner
  • plm.util.hmm.gaussian.GaussianArHmmClassEvaluator
  • plm.util.hmm.gaussian.GaussianArHmmRmseEvaluator
  • plm.util.hmm.gaussian.GaussianArHmmRunner
  • plm.util.hmm.gaussian.GaussianArHpHmmRunner
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