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	UniNormalFactor.sample(Randoms r)
Assignment	UniformFactor.sample(Randoms r)
Assignment	SkeletonFactor.sample(Randoms r)
Assignment	PottsTableFactor.sample(Randoms r)
Assignment	NormalFactor.sample(Randoms r)
Assignment	FactorGraph.sample(Randoms r)
Assignment	Factor.sample(Randoms r) Return an assignment sampled from this factor, interpreting it as an unnormalized probability distribution.
Assignment	CPT.sample(Randoms r)
Assignment	ConstantFactor.sample(Randoms r)
Assignment	BinaryUnaryFactor.sample(Randoms r)
Assignment	BetaFactor.sample(Randoms r)
Assignment	Assignment.sample(Randoms r)
Assignment	AbstractTableFactor.sample(Randoms r)
Assignment	AbstractFactor.sample(Randoms r)
Assignment	FactorGraph.sampleContinuousVars(Randoms r) Samples the continuous variables in this factor graph.
int	DiscreteFactor.sampleLocation(Randoms r)
int	CPT.sampleLocation(Randoms r)
int	AbstractTableFactor.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	WorkerRunnable.random
protected Randoms	TopicInferencer.random
protected Randoms	SimpleLDA.random
protected Randoms	PolylingualTopicModel.random
protected Randoms	NPTopicModel.random
protected Randoms	MarginalProbEstimator.random
protected Randoms	LDAHyper.random Deprecated.

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	TopicalNGrams.estimate(InstanceList documents, int numIterations, 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	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	Multinomial.randomFeatureSequence(Randoms r, int length)
FeatureSequence	Dirichlet.randomFeatureSequence(Randoms r, int length)
FeatureVector	Multinomial.randomFeatureVector(Randoms r, int size)
FeatureVector	Dirichlet.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 FeatureVectors.

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.