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## Uses of Class
cc.mallet.util.Randoms

Packages that use Randoms
cc.mallet.cluster.iterator |
cc.mallet.cluster.neighbor_evaluator |
cc.mallet.cluster.util |
cc.mallet.grmm.inference |
cc.mallet.grmm.types |
cc.mallet.pipe.iterator | Classes that generate instances from different kinds of input or data structures.
cc.mallet.topics |
cc.mallet.types | Fundamental MALLET types, including FeatureVector, Instance, Label etc.
cc.mallet.util | Miscellaneous utilities including command line processing, math functions, lexing, logging.

Uses of Randoms in cc.mallet.cluster.iterator

Fields in cc.mallet.cluster.iterator declared as Randoms
`protected Randoms` | `PairSampleIterator.random`

Methods in cc.mallet.cluster.iterator with parameters of type Randoms
`protected int[]` | `ClusterSampleIterator.sampleFromArray(int[] a, Randoms random, int minSize)` Samples a subset of elements from this array.
`protected int[][]` | `ClusterSampleIterator.sampleSplitFromArray(int[] a, Randoms random, int minSize)` Samples a two disjoint subset of elements from this array.

Constructors in cc.mallet.cluster.iterator with parameters of type Randoms
`ClusterSampleIterator(Clustering clustering, Randoms random, double positiveProportion, int numberSamples)`
`NodeClusterSampleIterator(Clustering clustering, Randoms random, double positiveProportion, int numberSamples)`
`PairSampleIterator(Clustering clustering, Randoms random, double positiveProportion, int numberSamples)`

Uses of Randoms in cc.mallet.cluster.neighbor_evaluator

Constructors in cc.mallet.cluster.neighbor_evaluator with parameters of type Randoms
`RandomEvaluator(Randoms random)`

Uses of Randoms in cc.mallet.cluster.util

Methods in cc.mallet.cluster.util with parameters of type Randoms
`static Clustering` | `ClusterUtils.createRandomClustering(InstanceList instances, Randoms random)`

Uses of Randoms in cc.mallet.grmm.inference

Methods in cc.mallet.grmm.inference with parameters of type Randoms
`static FactorGraph` | `RandomGraphs.createRandomChain(Randoms r, int length)`
`void` | `Sampler.setRandom(Randoms r)` Sets the random seed used by this sampler.
`void` | `GibbsSampler.setRandom(Randoms r)`
`void` | `ExactSampler.setRandom(Randoms r)`

Constructors in cc.mallet.grmm.inference with parameters of type Randoms
`ExactSampler(Randoms r)`
`GibbsSampler(Randoms r, int burnin)`

Uses of Randoms in cc.mallet.grmm.types

Methods in cc.mallet.grmm.types with parameters of type Randoms
`Assignment` | `SkeletonFactor.sample(Randoms r)`
`Assignment` | `CPT.sample(Randoms r)`
`Assignment` | `UniNormalFactor.sample(Randoms r)`
`Assignment` | `Factor.sample(Randoms r)` Return an assignment sampled from this factor, interpreting it as an unnormalized probability distribution.
`Assignment` | `NormalFactor.sample(Randoms r)`
`Assignment` | `BoltzmannUnaryFactor.sample(Randoms r)`
`Assignment` | `AbstractTableFactor.sample(Randoms r)`
`Assignment` | `ConstantFactor.sample(Randoms r)`
`Assignment` | `FactorGraph.sample(Randoms r)`
`Assignment` | `UniformFactor.sample(Randoms r)`
`Assignment` | `BinaryUnaryFactor.sample(Randoms r)`
`Assignment` | `PottsTableFactor.sample(Randoms r)`
`Assignment` | `Assignment.sample(Randoms r)`
`Assignment` | `BoltzmannPairFactor.sample(Randoms r)`
`Assignment` | `BetaFactor.sample(Randoms r)`
`Assignment` | `AbstractFactor.sample(Randoms r)`
`Assignment` | `FactorGraph.sampleContinuousVars(Randoms r)` Samples the continuous variables in this factor graph.
`int` | `CPT.sampleLocation(Randoms r)`
`int` | `AbstractTableFactor.sampleLocation(Randoms r)`
`int` | `DiscreteFactor.sampleLocation(Randoms r)`

Uses of Randoms in cc.mallet.pipe.iterator

Constructors in cc.mallet.pipe.iterator with parameters of type Randoms
`RandomFeatureVectorIterator(Randoms r, Alphabet vocab, java.lang.String[] classnames)`
`RandomFeatureVectorIterator(Randoms r, Dirichlet classCentroidDistribution, double classCentroidAvergeAlphaMean, double classCentroidAvergeAlphaVariance, double featureVectorSizePoissonLambda, double classInstanceCountPoissonLamba, java.lang.String[] classNames)`
`RandomFeatureVectorIterator(Randoms r, int vocabSize, int numClasses)`
`RandomTokenSequenceIterator(Randoms r, Alphabet vocab, java.lang.String[] classnames)`
`RandomTokenSequenceIterator(Randoms r, Dirichlet classCentroidDistribution, double classCentroidAvergeAlphaMean, double classCentroidAvergeAlphaVariance, double featureVectorSizePoissonLambda, double classInstanceCountPoissonLamba, java.lang.String[] classNames)`
`RandomTokenSequenceIterator(Randoms r, int vocabSize, int numClasses)`

Uses of Randoms in cc.mallet.topics

Fields in cc.mallet.topics declared as Randoms
`protected Randoms` | `TopicInferencer.random`
`protected Randoms` | `MarginalProbEstimator.random`
`protected Randoms` | `PolylingualTopicModel.random`
`protected Randoms` | `SimpleLDA.random`
`protected Randoms` | `LDAHyper.random` Deprecated.
`protected Randoms` | `WorkerRunnable.random`
`protected Randoms` | `NPTopicModel.random`

Methods in cc.mallet.topics with parameters of type Randoms
`void` | `LDA.addDocuments(InstanceList additionalDocuments, int numIterations, int showTopicsInterval, int outputModelInterval, java.lang.String outputModelFilename, Randoms r)` Deprecated.
`void` | `HierarchicalPAM.estimate(InstanceList documents, InstanceList testing, int numIterations, int showTopicsInterval, int outputModelInterval, int optimizeInterval, java.lang.String outputModelFilename, Randoms r)`
`void` | `PAM4L.estimate(InstanceList documents, int numIterations, int optimizeInterval, int showTopicsInterval, int outputModelInterval, java.lang.String outputModelFilename, Randoms r)`
`void` | `LDA.estimate(InstanceList documents, int numIterations, int showTopicsInterval, int outputModelInterval, java.lang.String outputModelFilename, Randoms r)` Deprecated.
`void` | `TopicalNGrams.estimate(InstanceList documents, int numIterations, int showTopicsInterval, int outputModelInterval, java.lang.String outputModelFilename, Randoms r)`
`void` | `LDA.estimate(int docIndexStart, int docIndexLength, int numIterations, int showTopicsInterval, int outputModelInterval, java.lang.String outputModelFilename, Randoms r)` Deprecated.
`void` | `HierarchicalLDA.initialize(InstanceList instances, InstanceList testing, int numLevels, Randoms random)`
`void` | `LDA.sampleTopicsForAllDocs(Randoms r)` Deprecated.
`void` | `LDA.sampleTopicsForDocs(int start, int length, Randoms r)` Deprecated.

Constructors in cc.mallet.topics with parameters of type Randoms
`LDAHyper(int numberOfTopics, double alphaSum, double beta, Randoms random)` Deprecated.
`LDAHyper(LabelAlphabet topicAlphabet, double alphaSum, double beta, Randoms random)` Deprecated.
`LDAStream(int numberOfTopics, double alphaSum, double beta, Randoms random)`
`LDAStream(LabelAlphabet topicAlphabet, double alphaSum, double beta, Randoms random)`
`PolylingualTopicModel(int numberOfTopics, double alphaSum, Randoms random)`
`PolylingualTopicModel(LabelAlphabet topicAlphabet, double alphaSum, Randoms random)`
`SimpleLDA(int numberOfTopics, double alphaSum, double beta, Randoms random)`
`SimpleLDA(LabelAlphabet topicAlphabet, double alphaSum, double beta, Randoms random)`
`WorkerRunnable(int numTopics, double[] alpha, double alphaSum, double beta, Randoms random, java.util.ArrayList<TopicAssignment> data, int[][] typeTopicCounts, int[] tokensPerTopic, int startDoc, int numDocs)`

Uses of Randoms in cc.mallet.types

Methods in cc.mallet.types with parameters of type Randoms
`void` | `InstanceList.hideSomeLabels(double proportionToHide, Randoms r)`
`Dirichlet` | `Dirichlet.randomDirichlet(Randoms r, double averageAlpha)`
`FeatureSequence` | `Dirichlet.randomFeatureSequence(Randoms r, int length)`
`FeatureSequence` | `Multinomial.randomFeatureSequence(Randoms r, int length)`
`FeatureVector` | `Dirichlet.randomFeatureVector(Randoms r, int size)`
`FeatureVector` | `Multinomial.randomFeatureVector(Randoms r, int size)`
`int` | `Multinomial.randomIndex(Randoms r)`
`Multinomial` | `Dirichlet.randomMultinomial(Randoms r)`
`java.lang.Object` | `Multinomial.randomObject(Randoms r)`
`protected double[]` | `Dirichlet.randomRawMultinomial(Randoms r)`
`TokenSequence` | `Dirichlet.randomTokenSequence(Randoms r, int length)`
`double[]` | `Dirichlet.randomVector(Randoms r)`

Constructors in cc.mallet.types with parameters of type Randoms
`InstanceList(Randoms r, Alphabet vocab, java.lang.String[] classNames, int meanInstancesPerLabel)`
`InstanceList(Randoms r, Dirichlet classCentroidDistribution, double classCentroidAverageAlphaMean, double classCentroidAverageAlphaVariance, double featureVectorSizePoissonLambda, double classInstanceCountPoissonLambda, java.lang.String[] classNames)` Creates a list consisting of randomly-generated `FeatureVector`s.
`InstanceList(Randoms r, int vocabSize, int numClasses)`

Uses of Randoms in cc.mallet.util

Methods in cc.mallet.util with parameters of type Randoms
`static FeatureVector` | `MVNormal.nextFeatureVector(Alphabet alphabet, double[] mean, double[] precision, Randoms random)`
`static double[]` | `MVNormal.nextMVNormal(double[] mean, double[] precision, Randoms random)` Sample a multivariate normal from a precision matrix (ie inverse covariance matrix)
`static double[][]` | `MVNormal.nextMVNormal(int n, double[] mean, double[] precision, Randoms random)`
`static double[]` | `MVNormal.nextMVNormalPosterior(double[] priorMean, double[] priorPrecisionDiagonal, double[] precision, double[] observedMean, int observations, Randoms random)`
`static double[]` | `MVNormal.nextMVNormalWithCholesky(double[] mean, double[] precisionLowerTriangular, Randoms random)`
`static double[]` | `MVNormal.nextWishart(double[] sqrtScaleMatrix, int dimension, int degreesOfFreedom, Randoms random)` A Wishart random variate, based on R code by Bill Venables.
`static double[]` | `MVNormal.nextWishartPosterior(double[] scatterMatrix, int observations, double[] priorPrecisionDiagonal, int priorDF, int dimension, Randoms random)`
`static double[]` | `MVNormal.nextZeroSumMVNormalWithCholesky(double[] mean, double[] precisionLowerTriangular, Randoms random)` Sample a vector x from N(m, (LL')-1, such that sum_i x_i = 0.

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