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Posted to commits@spark.apache.org by ma...@apache.org on 2014/01/22 23:02:00 UTC

[17/50] git commit: javadoc for sparsesvd

javadoc for sparsesvd


Project: http://git-wip-us.apache.org/repos/asf/incubator-spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-spark/commit/915d53f8
Tree: http://git-wip-us.apache.org/repos/asf/incubator-spark/tree/915d53f8
Diff: http://git-wip-us.apache.org/repos/asf/incubator-spark/diff/915d53f8

Branch: refs/heads/master
Commit: 915d53f8acb1f7ab14894b1255eb334b0812d9d3
Parents: c868d71
Author: Reza Zadeh <ri...@gmail.com>
Authored: Wed Jan 1 20:20:16 2014 -0800
Committer: Reza Zadeh <ri...@gmail.com>
Committed: Wed Jan 1 20:20:16 2014 -0800

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 .../scala/org/apache/spark/mllib/linalg/sparsesvd.scala   | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)
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http://git-wip-us.apache.org/repos/asf/incubator-spark/blob/915d53f8/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
index 83b2178..19173fd 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala
@@ -24,6 +24,7 @@ import org.apache.spark.rdd.RDD
 import org.jblas.{DoubleMatrix, Singular, MatrixFunctions}
 
 
+object SVD {
 /**
  * Singular Value Decomposition for Tall and Skinny matrices.
  * Given an m x n matrix A, this will compute matrices U, S, V such that
@@ -48,10 +49,13 @@ import org.jblas.{DoubleMatrix, Singular, MatrixFunctions}
  *
  * All input and output is expected in sparse matrix format, 1-indexed
  * as tuples of the form ((i,j),value) all in RDDs
+ *
+ * @param data RDD Matrix in sparse 1-index format ((int, int), value)
+ * @param m number of rows
+ * @param n number of columns
+ * @param min_svalue Recover singular values greater or equal to min_svalue
+ * @return Three sparse matrices: U, S, V such that A = USV^T
  */
-
-
-object SVD {
   def sparseSVD(
       data: RDD[((Int, Int), Double)],
       m: Int,