Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17032#discussion_r102899614
--- Diff: examples/src/main/r/ml/glm.R ---
@@ -25,12 +25,12 @@ library(SparkR)
sparkR.session(appName = "SparkR-ML-glm-example")
# $example on$
-t <- as.data.frame(Titanic)
-training <- createDataFrame(t)
+training <-
read.df("data/mllib/sample_multiclass_classification_data.txt", source =
"libsvm")
# Fit a generalized linear model of family "gaussian" with spark.glm
-gaussianDF <- training
-gaussianTestDF <- training
-gaussianGLM <- spark.glm(gaussianDF, Freq ~ Sex + Age, family = "gaussian")
+set.seed(2)
+gaussianDF <- sample(training, TRUE, 0.7)
+gaussianTestDF <- sample(training, TRUE, 0.3)
--- End diff --
`sample` could duplicate the same row in both training and test set.
I think we should use randomSplit instead.
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