Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11319#discussion_r53923176
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/QuantileDiscretizer.scala ---
@@ -103,6 +103,13 @@ final class QuantileDiscretizer(override val uid:
String)
@Since("1.6.0")
object QuantileDiscretizer extends
DefaultParamsReadable[QuantileDiscretizer] with Logging {
+
+ /**
+ * Minimum number of samples required for finding splits, regardless of
number of bins. If
+ * the dataset has less rows than this value, the entire dataset column
will be used.
+ */
+ val minSamplesRequired: Int = 10000
--- End diff --
less rows -> fewer rows
entire dataset column -> entire dataset?
10000 just isn't that big. A dummy data set in a test would be, what, a
megabyte in memory? Am I missing a bigger problem there?
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