LightLda LightLda LightLda Class


The LDA transform implements LightLDA, a state-of-the-art implementation of Latent Dirichlet Allocation.

public sealed class LightLda : Microsoft.ML.ILearningPipelineItem, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput
type LightLda = class
    interface CommonInputs.ITransformInput
    interface ILearningPipelineItem
Public NotInheritable Class LightLda
Implements CommonInputs.ITransformInput, ILearningPipelineItem


LightLda() LightLda() LightLda()
LightLda(String[]) LightLda(String[]) LightLda(String[])
LightLda(ValueTuple<String,String>[]) LightLda(ValueTuple<String,String>[]) LightLda(ValueTuple<String,String>[])


AlphaSum AlphaSum AlphaSum

Dirichlet prior on document-topic vectors

Beta Beta Beta

Dirichlet prior on vocab-topic vectors

Column Column Column

New column definition(s) (optional form: name:srcs)

Data Data Data

Input dataset

LikelihoodInterval LikelihoodInterval LikelihoodInterval

Compute log likelihood over local dataset on this iteration interval

Mhstep Mhstep Mhstep

Number of Metropolis Hasting step

NumBurninIterations NumBurninIterations NumBurninIterations

The number of burn-in iterations

NumIterations NumIterations NumIterations

Number of iterations

NumMaxDocToken NumMaxDocToken NumMaxDocToken

The threshold of maximum count of tokens per doc

NumSummaryTermPerTopic NumSummaryTermPerTopic NumSummaryTermPerTopic

The number of words to summarize the topic

NumThreads NumThreads NumThreads

The number of training threads. Default value depends on number of logical processors.

NumTopic NumTopic NumTopic

The number of topics in the LDA

OutputTopicWordSummary OutputTopicWordSummary OutputTopicWordSummary

Whether to output the topic-word summary in text format

ResetRandomGenerator ResetRandomGenerator ResetRandomGenerator

Reset the random number generator for each document


AddColumn(String) AddColumn(String) AddColumn(String)
AddColumn(String, String) AddColumn(String, String) AddColumn(String, String)
ApplyStep(ILearningPipelineStep, Experiment) ApplyStep(ILearningPipelineStep, Experiment) ApplyStep(ILearningPipelineStep, Experiment)
GetInputData() GetInputData() GetInputData()

Applies to