BIDMach.models

LDA

object LDA

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  1. class Options extends Opts

  2. trait Opts extends FactorModel.Opts

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  1. final def !=(arg0: Any): Boolean

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  12. def learnBatch(mat0: Mat, d: Int = 256): (Learner, Learner.Options with Opts with datasources.MatDS.Opts with updaters.BatchNorm.Opts)

    Batch Variational Bayes LDA algorithm with a matrix datasource.

  13. def learnFPar(nstart: Int = FilesDS.encodeDate(2012,3,1,0), nend: Int = FilesDS.encodeDate(2012,12,1,0), d: Int = 256): (ParLearnerF, ParLearner.Options with Opts with datasources.SFilesDS.Opts with updaters.IncNorm.Opts)

    Parallel online LDA algorithm with one file datasource.

  14. def learnFParx(nstart: Int = FilesDS.encodeDate(2012,3,1,0), nend: Int = FilesDS.encodeDate(2012,12,1,0), d: Int = 256): (ParLearnerxF, ParLearner.Options with Opts with datasources.SFilesDS.Opts with updaters.IncNorm.Opts)

    Parallel online LDA algorithm with multiple file datasources.

  15. def learnPar(mat0: Mat, d: Int = 256): (ParLearnerF, ParLearner.Options with Opts with datasources.MatDS.Opts with updaters.IncNorm.Opts)

    Parallel online LDA algorithm with a matrix datasource.

  16. def learner(fnames: List[(Int) ⇒ String], d: Int): (Learner, Learner.Options with Opts with datasources.SFilesDS.Opts with updaters.IncNorm.Opts)

    Online Variational Bayes LDA algorithm with a files dataSource.

  17. def learner(mat0: Mat, d: Int): (Learner, Learner.Options with Opts with datasources.MatDS.Opts with updaters.IncNorm.Opts)

    Online Variational Bayes LDA algorithm with a matrix datasource.

  18. def mkLDAmodel(fopts: Model.Opts): LDA

    Creates a new LDA model.

  19. def mkUpdater(nopts: updaters.Updater.Opts): IncNorm

    Creates a new IncNorm updater.

  20. final def ne(arg0: AnyRef): Boolean

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