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

Jump to bottom

[doc] update the jvm tutorial to 1.6.1 [skip ci] #7834

Merged
merged 1 commit into from Apr 24, 2022
Merged

[doc] update the jvm tutorial to 1.6.1 [skip ci] #7834

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.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
4 changes: 2 additions & 2 deletions doc/jvm/xgboost4j_spark_gpu_tutorial.rst
View file
Open in desktop
@@ -1,5 +1,5 @@
#############################################
XGBoost4J-Spark-GPU Tutorial (version 1.6.0+)
XGBoost4J-Spark-GPU Tutorial (version 1.6.1+)
#############################################

**XGBoost4J-Spark-GPU** is an open source library aiming to accelerate distributed XGBoost training on Apache Spark cluster from
Expand Down Expand Up @@ -220,7 +220,7 @@ application jar is iris-1.0.0.jar

cudf_version=22.02.0
rapids_version=22.02.0
xgboost_version=1.6.0
xgboost_version=1.6.1
main_class=Iris
app_jar=iris-1.0.0.jar

Expand Down
2 changes: 1 addition & 1 deletion doc/jvm/xgboost4j_spark_tutorial.rst
View file
Open in desktop
Expand Up @@ -129,7 +129,7 @@ labels. A DataFrame like this (containing vector-represented features and numeri

.. note::

There is no need to assemble feature columns from version 1.6.0+. Instead, users can specify an array of
There is no need to assemble feature columns from version 1.6.1+. Instead, users can specify an array of
feture column names by ``setFeaturesCol(value: Array[String])`` and XGBoost4j-Spark will do it.
Copy link

Choose a reason for hiding this comment

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

typo: "feture" -> "feature"

Copy link

Choose a reason for hiding this comment

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

also, unrelated, but it would be helpful to comment whether is it possible to use the new categorical feature support in 1.6.X from xgboost4j.

Copy link
Member

Choose a reason for hiding this comment

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

Thank you for the suggestion. It's Python only at the moment and is considered experimental. We will continue to expand it.


Dealing with missing values
Expand Down