Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/3095#discussion_r19988621
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala ---
@@ -278,8 +278,18 @@ class PythonMLLibAPI extends Serializable {
rank: Int,
iterations: Int,
lambda: Double,
- blocks: Int): MatrixFactorizationModel = {
- new MatrixFactorizationModelWrapper(ALS.train(ratings.rdd, rank,
iterations, lambda, blocks))
+ blocks: Int,
+ nonnegative: Boolean,
+ seed: java.lang.Long): MatrixFactorizationModel = {
+ if (seed == null) {
+ new MatrixFactorizationModelWrapper(
+ // if the seed coming from python is None/null, let ALS use the
+ // default, which is to use System.nanoTime
+ ALS.train(ratings.rdd, rank, iterations, lambda, blocks,
nonnegative))
--- End diff --
Let's use setters so we don't need to add many static methods.
~~~
val als = new ALS()
.setRank(rank)
.setIterations(iterations)
.setLambda(lambda)
.setBlocks(blocks)
.setNonnegative(nonnegative)
if (seed != null) als.setSeed(seed)
val model = als.run(ratings.rdd)
new MatrixFactorizationModelWrapper(model)
~~~
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