Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[SPARKR][DOC] update doc for fpgrowth #17526

Closed
wants to merge 2 commits into from
Closed

[SPARKR][DOC] update doc for fpgrowth #17526

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
5fee9e7
update doc
felixcheung Apr 4, 2017
e4e03ea
dead space
felixcheung Apr 4, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 1 addition & 5 deletions R/pkg/R/mllib_clustering.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -498,11 +498,7 @@ setMethod("write.ml", signature(object = "KMeansModel", path = "character"),
#' @export
#' @examples
#' \dontrun{
#' # nolint start
#' # An example "path/to/file" can be
#' # paste0(Sys.getenv("SPARK_HOME"), "/data/mllib/sample_lda_libsvm_data.txt")
#' # nolint end
#' text <- read.df("path/to/file", source = "libsvm")
#' text <- read.df("data/mllib/sample_lda_libsvm_data.txt", source = "libsvm")
#' model <- spark.lda(data = text, optimizer = "em")
#'
#' # get a summary of the model
Expand Down
4 changes: 4 additions & 0 deletions R/pkg/R/mllib_fpm.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,10 @@ setClass("FPGrowthModel", slots = list(jobj = "jobj"))
#' FP-growth
#'
#' A parallel FP-growth algorithm to mine frequent itemsets.
#' \code{spark.fpGrowth} fits a FP-growth model on a SparkDataFrame. Users can
#' \code{spark.freqItemsets} to get frequent itemsets, \code{spark.associationRules} to get
#' association rules, \code{predict} to make predictions on new data based on generated association
#' rules, and \code{write.ml}/\code{read.ml} to save/load fitted models.
#' For more details, see
#' \href{https://spark.apache.org/docs/latest/mllib-frequent-pattern-mining.html#fp-growth}{
#' FP-growth}.
Expand Down