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author | Reza Zadeh <rizlar@gmail.com> | 2013-12-27 01:51:19 -0500 |
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committer | Reza Zadeh <rizlar@gmail.com> | 2013-12-27 01:51:19 -0500 |
commit | 642ab5c1e1ba98833265447447702c3c39fb2d40 (patch) | |
tree | c058583cc93d78823422f360035e9124d65f98dd /mllib/src/main | |
parent | 3369c2d48795d831acd841b8ecb67b5a84083883 (diff) | |
download | spark-642ab5c1e1ba98833265447447702c3c39fb2d40.tar.gz spark-642ab5c1e1ba98833265447447702c3c39fb2d40.tar.bz2 spark-642ab5c1e1ba98833265447447702c3c39fb2d40.zip |
initial large scale testing begin
Diffstat (limited to 'mllib/src/main')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/linalg/sparsesvd.scala | 8 |
1 files changed, 4 insertions, 4 deletions
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 1c9f67e265..edf715dc19 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 @@ -32,8 +32,8 @@ import org.jblas.{DoubleMatrix, Singular, MatrixFunctions} * There is no restriction on m, but we require n^2 doubles to fit in memory. * Further, n should be less than m. * - * This is computed by first computing A'A = V S^2 V', - * computing locally on that (since n x n is small), + * The decomposition is computed by first computing A'A = V S^2 V', + * computing svd locally on that (since n x n is small), * from which we recover S and V. * Then we compute U via easy matrix multiplication * as U = A * V * S^-1 @@ -43,8 +43,8 @@ import org.jblas.{DoubleMatrix, Singular, MatrixFunctions} * such values, then the dimensions of the return will be: * * S is k x k and diagonal, holding the singular values on diagonal - * U is m x k and satisfies U'U = eye(k,k) - * V is n x k and satisfies V'V = eye(k,k) + * U is m x k and satisfies U'U = eye(k) + * V is n x k and satisfies V'V = eye(k) * * All input and output is expected in sparse matrix format, 1-indexed * as tuples of the form ((i,j),value) all in RDDs |