Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/9180#discussion_r42923610
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala ---
@@ -125,6 +124,58 @@ object LinearDataGenerator {
}
/**
+ * @param intercept Data intercept
+ * @param weights Weights to be applied.
+ * @param xMean the mean of the generated features. Lots of time, if the
features are not properly
+ * standardized, the algorithm with poor implementation
will have difficulty
+ * to converge.
+ * @param xVariance the variance of the generated features.
+ * @param nPoints Number of points in sample.
+ * @param seed Random seed
+ * @param eps Epsilon scaling factor.
+ * @return Seq of LabeledPoint includes sparse vectors..
+ */
--- End diff --
How about consolidate with `LinearDataGenerator`, and add `sparsity = 1.0`
as param to control if it's sparse feature?
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