Github user davideis commented on a diff in the pull request:
https://github.com/apache/spark/pull/18022#discussion_r117265969
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -1624,15 +1628,15 @@ object ALS extends DefaultParamsReadable[ALS] with
Logging {
val srcFactor = sortedSrcFactors(blockId)(localIndex)
val rating = ratings(i)
if (implicitPrefs) {
- // Extension to the original paper to handle b < 0.
confidence is a function of |b|
- // instead so that it is never negative. c1 is confidence -
1.0.
+ // Extension to the original paper to handle rating < 0.
confidence is a function
+ // of |rating| instead so that it is never negative. c1 is
confidence - 1.
val c1 = alpha * math.abs(rating)
- // For rating <= 0, the corresponding preference is 0. So
the term below is only added
- // for rating > 0. Because YtY is already added, we need to
adjust the scaling here.
- if (rating > 0) {
+ // For rating <= 0, the corresponding preference is 0. So
the second argument of add
+ // is only there for rating > 0.
+ if (rating > 0.0) {
numExplicits += 1
- ls.add(srcFactor, (c1 + 1.0) / c1, c1)
}
+ ls.add(srcFactor, if (rating > 0.0) 1.0 + c1 else 0.0, c1)
--- End diff --
Correct, this is the crux of the change (moving outside of the if
condition). Changing the arguments was more to be less confusing and more
direct, since it was very confusing to me before where the ``(1+c1)/c1`` was
coming from and then when it is actually used in ``add``, it gets multiplied by
``c1``, which is a wasted operation and may not even exactly yield ``1+c1`` in
the end.
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