Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/88#discussion_r10772392
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala ---
@@ -38,20 +39,113 @@ class SVD {
this
}
- /**
+ /**
+ * Singular values smaller than this value
+ * relative to the largest singular value are considered zero
+ */
+ def setReciprocalConditionNumber(smallS: Double): SVD = {
+ this.rCond = smallS
+ this
+ }
+
+ /**
+ * Should U be computed?
+ */
+ def setComputeU(compU: Boolean): SVD = {
+ this.computeU = compU
+ this
+ }
+
+ /**
* Compute SVD using the current set parameters
*/
- def compute(matrix: SparseMatrix) : MatrixSVD = {
- SVD.sparseSVD(matrix, k)
+ def compute(matrix: TallSkinnyDenseMatrix) : TallSkinnyMatrixSVD = {
+ denseSVD(matrix)
}
-}
+ /**
+ * Compute SVD using the current set parameters
+ * Returns (U, S, V) such that A = USV^T
+ * U is a row-by-row dense matrix
+ * S is a simple double array of singular values
+ * V is a 2d array matrix
+ * See denseSVD for more documentation
+ */
+ def compute(matrix: RDD[Array[Double]]) :
+ (RDD[Array[Double]], Array[Double], Array[Array[Double]]) = {
+ denseSVD(matrix)
+ }
+
+ /**
+ * Compute SVD with default parameter for computeU = true.
+ * See full paramter definition of sparseSVD for more description.
--- End diff --
"paramter" -> "parameter"
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