From 050c20cc9084bd6ef738fd808dad43139250f316 Mon Sep 17 00:00:00 2001
From: actuaryzhang <actuaryzhang10@gmail.com>
Date: Fri, 3 Feb 2017 18:02:10 -0800
Subject: [PATCH] [SPARK-19386][SPARKR][FOLLOWUP] fix error in vignettes
## What changes were proposed in this pull request?
Current version has error in vignettes:
```
model <- spark.bisectingKmeans(df, Sepal_Length ~ Sepal_Width, k = 4)
summary(kmeansModel)
```
`kmeansModel` does not exist...
felixcheung wangmiao1981
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes #16799 from actuaryzhang/sparkRVignettes.
---
R/pkg/vignettes/sparkr-vignettes.Rmd | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/R/pkg/vignettes/sparkr-vignettes.Rmd b/R/pkg/vignettes/sparkr-vignettes.Rmd
index a7cac2f503..f13e0b3a18 100644
--- a/R/pkg/vignettes/sparkr-vignettes.Rmd
+++ b/R/pkg/vignettes/sparkr-vignettes.Rmd
@@ -744,10 +744,10 @@ predictions <- predict(rfModel, df)
`spark.bisectingKmeans` is a kind of [hierarchical clustering](https://en.wikipedia.org/wiki/Hierarchical_clustering) using a divisive (or "top-down") approach: all observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.
-```{r}
+```{r, warning=FALSE}
df <- createDataFrame(iris)
model <- spark.bisectingKmeans(df, Sepal_Length ~ Sepal_Width, k = 4)
-summary(kmeansModel)
+summary(model)
fitted <- predict(model, df)
head(select(fitted, "Sepal_Length", "prediction"))
```
--
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