From b511638ca10a4719e2df6f6e7571fd95a03aaf0a Mon Sep 17 00:00:00 2001 From: Philip Hyunsu Cho Date: Mon, 6 May 2019 14:21:49 -0700 Subject: [PATCH] Fix list formatting in missing value tutorial in XGBoost4J-Spark --- doc/jvm/xgboost4j_spark_tutorial.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/doc/jvm/xgboost4j_spark_tutorial.rst b/doc/jvm/xgboost4j_spark_tutorial.rst index a3208f520..c3ca3dda3 100644 --- a/doc/jvm/xgboost4j_spark_tutorial.rst +++ b/doc/jvm/xgboost4j_spark_tutorial.rst @@ -160,6 +160,7 @@ Strategies to handle missing values (and therefore overcome issues as above): In the case that a feature column contains missing values for any reason (could be related to business logic / wrong data ingestion process / etc.), the user should decide on a strategy of how to handle it. The choice of approach depends on the value representing 'missing' which fall into four different categories: + 1. 0. 2. NaN. 3. Null.