Github user felixcheung commented on a diff in the pull request: https://github.com/apache/spark/pull/14229#discussion_r72880758 --- Diff: R/pkg/R/mllib.R --- @@ -596,6 +688,68 @@ setMethod("spark.survreg", signature(data = "SparkDataFrame", formula = "formula return(new("AFTSurvivalRegressionModel", jobj = jobj)) }) +#' Latent Dirichlet Allocation +#' +#' \code{spark.lda} fits a Latent Dirichlet Allocation model on a SparkDataFrame. Users can call +#' \code{summary} to get a summary of the fitted LDA model, \code{spark.posterior} to compute +#' posterior probabilities on new data, \code{spark.perplexity} to compute log perplexity on new +#' data and \code{write.ml}/\code{read.ml} to save/load fitted models. +#' +#' @param data A SparkDataFrame for training +#' @param features Features column name, default "features". Either Vector format column or String +#' format column are accepted. +#' @param k Number of topics, default 10 +#' @param maxIter Maximum iterations, default 20 +#' @param optimizer Optimizer to train an LDA model, "online" or "em", default "online" +#' @param subsamplingRate (For online optimizer) Fraction of the corpus to be sampled and used in +# each iteration of mini-batch gradient descent, in range (0, 1], default 0.05 +#' @param topicConcentration concentration parameter (commonly named \code{beta} or \code{eta}) for +#' the prior placed on topic distributions over terms, default -1 to set automatically on the +#' Spark side. Use \code{summary} to retrieve the effective topicConcentration. +#' @param docConcentration concentration parameter (commonly named \code{alpha}) for the +#' prior placed on documents distributions over topics (\code{theta}), default -1 to set +#' automatically on the Spark side. Use \code{summary} to retrieve the effective +#' docConcentration. +#' @param customizedStopWords stopwords that need to be removed from the given corpus. Only effected +#' given training data with string format column. +#' @param maxVocabSize maximum vocabulary size, default 1 << 18 +#' @return \code{spark.lda} returns a fitted Latent Dirichlet Allocation model +#' @rdname spark.lda +#' @seealso survival: \url{https://cran.r-project.org/web/packages/topicmodels/} --- End diff -- is this the right link?
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