Skip to content

[SPARK-19714][DOCS] Clarify Bucketizer handling of invalid input #23003

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
srowen wants to merge 1 commit into from
Closed

[SPARK-19714][DOCS] Clarify Bucketizer handling of invalid input #23003

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
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: 4 additions & 2 deletions mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,8 @@ final class Bucketizer @Since("1.4.0") (@Since("1.4.0") override val uid: String
def setOutputCol(value: String): this.type = set(outputCol, value)

/**
* Param for how to handle invalid entries. Options are 'skip' (filter out rows with
* Param for how to handle invalid entries containing NaN values. Values outside the splits
* will always be treated as errors. Options are 'skip' (filter out rows with
* invalid values), 'error' (throw an error), or 'keep' (keep invalid values in a special
* additional bucket). Note that in the multiple column case, the invalid handling is applied
* to all columns. That said for 'error' it will throw an error if any invalids are found in
Expand All @@ -99,7 +100,8 @@ final class Bucketizer @Since("1.4.0") (@Since("1.4.0") override val uid: String
*/
@Since("2.1.0")
override val handleInvalid: Param[String] = new Param[String](this, "handleInvalid",
"how to handle invalid entries. Options are skip (filter out rows with invalid values), " +
"how to handle invalid entries containing NaN values. Values outside the splits will always " +
"be treated as errorsOptions are skip (filter out rows with invalid values), " +
"error (throw an error), or keep (keep invalid values in a special additional bucket).",
ParamValidators.inArray(Bucketizer.supportedHandleInvalids))

Expand Down
5 changes: 3 additions & 2 deletions python/pyspark/ml/feature.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -361,8 +361,9 @@ class Bucketizer(JavaTransformer, HasInputCol, HasOutputCol, HasHandleInvalid,
"splits specified will be treated as errors.",
typeConverter=TypeConverters.toListFloat)

handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. " +
"Options are 'skip' (filter out rows with invalid values), " +
handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries "
"containing NaN values. Values outside the splits will always be treated "
"as errors. Options are 'skip' (filter out rows with invalid values), " +
"'error' (throw an error), or 'keep' (keep invalid values in a special " +
"additional bucket).",
typeConverter=TypeConverters.toString)
Expand Down