Github user rnowling commented on a diff in the pull request:
https://github.com/apache/spark/pull/2494#discussion_r17880653
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/IDF.scala ---
@@ -123,7 +134,17 @@ private object IDF {
val inv = new Array[Double](n)
var j = 0
while (j < n) {
- inv(j) = math.log((m + 1.0)/ (df(j) + 1.0))
+ /*
+ * If the term is not present in the minimum
+ * number of documents, set IDF to 0. This
+ * will cause multiplication in IDFModel to
+ * set TF-IDF to 0.
+ */
+ if(df(j) >= minimumOccurence) {
+ inv(j) = math.log((m + 1.0)/ (df(j) + 1.0))
+ } else {
--- End diff --
Yes, the branch is needed. I don't modify the df vector -- I perform the
filtering in idf(). I should probably have clarified the commit comments to
explain that the IDF is set to 0, not the DF.
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