Github user feynmanliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7307#discussion_r34314893
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/clustering/LDA.scala
---
@@ -77,37 +89,47 @@ class LDA private (
* Concentration parameter (commonly named "alpha") for the prior placed
on documents'
* distributions over topics ("theta").
*
- * This is the parameter to a symmetric Dirichlet distribution.
+ * This is the parameter to a Dirichlet distribution.
*/
- def getDocConcentration: Double = this.docConcentration
+ def getDocConcentration: Vector = this.docConcentration
/**
* Concentration parameter (commonly named "alpha") for the prior placed
on documents'
* distributions over topics ("theta").
*
- * This is the parameter to a symmetric Dirichlet distribution, where
larger values
- * mean more smoothing (more regularization).
+ * This is the parameter to a Dirichlet distribution, where larger
values mean more smoothing
+ * (more regularization).
*
- * If set to -1, then docConcentration is set automatically.
- * (default = -1 = automatic)
+ * If set to a vector of -1, then docConcentration is set automatically.
--- End diff --
Empty vectors are funny... you can only create a sparse empty vector but
not a dense one. Do you think that's okay?
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