Skip to content

[SPARK-16144][SPARKR] update R API doc for mllib #13993

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

Closed
felixcheung wants to merge 2 commits into from
Closed

[SPARK-16144][SPARKR] update R API doc for mllib #13993

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
afc8ebe
update doc for mlliv
felixcheung Jun 30, 2016
1f9552e
update
felixcheung Jun 30, 2016
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
Next Next commit
update doc for mlliv
  • Loading branch information
@felixcheung
felixcheung committed Jun 30, 2016
commit afc8ebefd5904ff3f71a0257b89db9f1b6ffdf0d
2 changes: 0 additions & 2 deletions R/pkg/R/generics.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1247,7 +1247,6 @@ setGeneric("spark.glm", function(data, formula, ...) { standardGeneric("spark.gl
#' @export
setGeneric("glm")

#' predict
#' @rdname predict
#' @export
setGeneric("predict", function(object, ...) { standardGeneric("predict") })
Expand All @@ -1272,7 +1271,6 @@ setGeneric("spark.naiveBayes", function(data, formula, ...) { standardGeneric("s
#' @export
setGeneric("spark.survreg", function(data, formula, ...) { standardGeneric("spark.survreg") })

#' write.ml
#' @rdname write.ml
#' @export
setGeneric("write.ml", function(object, path, ...) { standardGeneric("write.ml") })
34 changes: 28 additions & 6 deletions R/pkg/R/mllib.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,28 @@ setClass("AFTSurvivalRegressionModel", representation(jobj = "jobj"))
#' @note KMeansModel since 2.0.0
setClass("KMeansModel", representation(jobj = "jobj"))

#' Saves the machine learning model to the input path
Copy link
Contributor

@yanboliang yanboliang Jun 30, 2016

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I vote to use MLlib model rather than machine learning model in the whole context.

#'
#' Saves the machine learning model to the input path. For more information, see the specific
#' machine learning model below.
#' @rdname write.ml
#' @name write.ml
#' @export
#' @seealso \link{spark.glm}, \link{spark.kmeans}, \link{spark.naiveBayes}, \link{spark.survreg}
#' @seealso \link{read.ml}
Copy link
Contributor

@yanboliang yanboliang Jun 30, 2016

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

It's better to add @seealso \link{write.ml} in the docs of read.ml.

NULL

#' Predicted values based on a machine learning model
Copy link
Contributor

@yanboliang yanboliang Jun 30, 2016

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Makes predictions from a MLlib model will be better?

#'
#' Predicted values based on a machine learning model. For more information, see the specific
#' machine learning model below.
#' @rdname predict
#' @name predict
#' @export
#' @seealso \link{spark.glm}, \link{spark.kmeans}, \link{spark.naiveBayes}, \link{spark.survreg}
#' @seealso \link{read.ml}
Copy link
Contributor

@yanboliang yanboliang Jun 30, 2016

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

It's not necessary to link read.ml to predict, I think here is typo.

NULL

#' Generalized Linear Models
#'
#' Fits generalized linear model against a Spark DataFrame. Users can print, make predictions on the
Expand Down Expand Up @@ -145,7 +167,7 @@ setMethod("glm", signature(formula = "formula", family = "ANY", data = "SparkDat
})

# Returns the summary of a model produced by glm() or spark.glm(), similarly to R's summary().
#'

#' @param object A fitted generalized linear model
#' @return \code{summary} returns a summary object of the fitted model, a list of components
#' including at least the coefficients, null/residual deviance, null/residual degrees
Expand Down Expand Up @@ -185,7 +207,7 @@ setMethod("summary", signature(object = "GeneralizedLinearRegressionModel"),
})

# Prints the summary of GeneralizedLinearRegressionModel
#'

#' @rdname spark.glm
#' @param x Summary object of fitted generalized linear model returned by \code{summary} function
#' @export
Expand Down Expand Up @@ -343,7 +365,7 @@ setMethod("fitted", signature(object = "KMeansModel"),
})

# Get the summary of a k-means model
#'

#' @param object A fitted k-means model
#' @return \code{summary} returns the model's coefficients, size and cluster
#' @rdname spark.kmeans
Expand All @@ -370,7 +392,7 @@ setMethod("summary", signature(object = "KMeansModel"),
})

# Predicted values based on a k-means model
#'

#' @return \code{predict} returns the predicted values based on a k-means model
#' @rdname spark.kmeans
#' @export
Expand Down Expand Up @@ -463,7 +485,7 @@ setMethod("write.ml", signature(object = "AFTSurvivalRegressionModel", path = "c
})

# Saves the generalized linear model to the input path.
#'

#' @param path The directory where the model is saved
#' @param overwrite Overwrites or not if the output path already exists. Default is FALSE
#' which means throw exception if the output path exists.
Expand All @@ -481,7 +503,7 @@ setMethod("write.ml", signature(object = "GeneralizedLinearRegressionModel", pat
})

# Save fitted MLlib model to the input path
#'

#' @param path The directory where the model is saved
#' @param overwrite Overwrites or not if the output path already exists. Default is FALSE
#' which means throw exception if the output path exists.
Expand Down