Github user tmyklebu commented on a diff in the pull request:
https://github.com/apache/spark/pull/460#discussion_r12005355
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala ---
@@ -537,6 +566,34 @@ object ALS {
* in the form of (userID, productID, rating) pairs. We approximate the
ratings matrix as the
* product of two lower-rank matrices of a given rank (number of
features). To solve for these
* features, we run a given number of iterations of ALS. This is done
using a level of
+ * parallelism given by `blocks`, partitioning the data using the
Partitioner `partitioner`.
+ *
+ * @param ratings RDD of (userID, productID, rating) pairs
+ * @param rank number of features to use
+ * @param iterations number of iterations of ALS (recommended: 10-20)
+ * @param lambda regularization factor (recommended: 0.01)
+ * @param blocks level of parallelism to split computation into
+ * @param seed random seed
+ * @param nonnegative Whether to impose nonnegativity constraints
+ */
+ def train(
+ ratings: RDD[Rating],
+ rank: Int,
+ iterations: Int,
+ lambda: Double,
+ blocks: Int,
+ seed: Long,
+ nonnegative: Boolean) = {
--- End diff --
@mengxr I did that, but it meant no longer marking ALS's constructor
private.
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