Github user debasish83 commented on a diff in the pull request:
https://github.com/apache/spark/pull/3098#discussion_r27529347
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
---
@@ -35,33 +41,33 @@ import org.apache.spark.rdd.RDD
* and the features computed for this product.
*/
class MatrixFactorizationModel private[mllib] (
- val rank: Int,
- val userFeatures: RDD[(Int, Array[Double])],
- val productFeatures: RDD[(Int, Array[Double])]) extends Serializable {
+ val rank: Int,
+ val userFeatures: RDD[(Int, Array[Double])],
+ val productFeatures: RDD[(Int, Array[Double])]) extends Serializable {
/** Predict the rating of one user for one product. */
def predict(user: Int, product: Int): Double = {
- val userVector = new DoubleMatrix(userFeatures.lookup(user).head)
- val productVector = new
DoubleMatrix(productFeatures.lookup(product).head)
- userVector.dot(productVector)
+ val userVector = Vectors.dense(userFeatures.lookup(user).head)
--- End diff --
I cleaned netlib.ddot to BLAS.dot...they will be same for these cases
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