documentation and cleanup

apache · Mar 20, 2014 · 3f23271 · 3f23271
1 parent b025ab2
commit 3f23271
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Showing 2 changed files with 1 addition and 5 deletions.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/PCA.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/PCA.scala
@@ -65,13 +65,11 @@ class PCA {
    * singular value decomposition (SVD) algorithm. 
    *
    * @param matrix dense matrix to perform PCA on
-   * @param k Recover k principal components
    * @return An nxk matrix with principal components in columns. Columns are inner arrays
    */
   private def computePCA(matrix: TallSkinnyDenseMatrix): Array[Array[Double]] = {
     val m = matrix.m
     val n = matrix.n
-    val sc = matrix.rows.sparkContext
 
     if (m <= 0 || n <= 0) {
       throw new IllegalArgumentException("Expecting a well-formed matrix: m=$m n=$n")
@@ -90,12 +88,10 @@ class PCA {
    * singular value decomposition (SVD) algorithm. 
    *
    * @param matrix dense matrix to perform pca on
-   * @param k Recover k principal components
    * @return An nxk matrix of principal components
    */
   private def computePCA(matrix: RDD[Array[Double]]): Array[Array[Double]] = {
     val n = matrix.first.size
-    val sc = matrix.sparkContext
 
     // compute column sums and normalize matrix
     val colSumsTemp = matrix.map((_, 1)).fold((Array.ofDim[Double](n), 0)) { (a, b) => 

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala
@@ -280,7 +280,7 @@ class SVD {
       throw new IllegalArgumentException("Must request up to n singular values")
     }
 
-    // Compute A^T A, assuming rows are sparse enough to fit in memory
+   // Compute A^T A, assuming rows are sparse enough to fit in memory
     val rows = data.map(entry =>
             (entry.i, (entry.j, entry.mval))).groupByKey()
     val emits = rows.flatMap{ case (rowind, cols)  =>