diff options
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala index 038edc3521..90ac252226 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala @@ -746,7 +746,7 @@ object ALS { * @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 alpha confidence parameter (only applies when immplicitPrefs = true) + * @param alpha confidence parameter * @param seed random seed */ def trainImplicit( @@ -773,7 +773,7 @@ object ALS { * @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 alpha confidence parameter (only applies when immplicitPrefs = true) + * @param alpha confidence parameter */ def trainImplicit( ratings: RDD[Rating], @@ -797,6 +797,7 @@ object ALS { * @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 alpha confidence parameter */ def trainImplicit(ratings: RDD[Rating], rank: Int, iterations: Int, lambda: Double, alpha: Double) : MatrixFactorizationModel = { |