[GitHub] spark pull request #15342: [SPARK-11560] [MLLIB] Optimize KMeans implementat...

[yanboliang <gi...@git.apache.org>]

Github user yanboliang commented on a diff in the pull request:

    https://github.com/apache/spark/pull/15342#discussion_r82619472
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
    @@ -43,21 +43,21 @@ import org.apache.spark.util.random.XORShiftRandom
     class KMeans private (
         private var k: Int,
         private var maxIterations: Int,
    -    private var runs: Int,
         private var initializationMode: String,
         private var initializationSteps: Int,
         private var epsilon: Double,
         private var seed: Long) extends Serializable with Logging {
     
       /**
    -   * Constructs a KMeans instance with default parameters: {k: 2, maxIterations: 20, runs: 1,
    +   * Constructs a KMeans instance with default parameters: {k: 2, maxIterations: 20,
        * initializationMode: "k-means||", initializationSteps: 2, epsilon: 1e-4, seed: random}.
        */
       @Since("0.8.0")
    -  def this() = this(2, 20, 1, KMeans.K_MEANS_PARALLEL, 2, 1e-4, Utils.random.nextLong())
    +  def this() = this(2, 20, KMeans.K_MEANS_PARALLEL, 2, 1e-4, Utils.random.nextLong())
     
       /**
    -   * Number of clusters to create (k).
    +   * Number of clusters to create (k). Note that if the input has fewer than k elements,
    +   * then it's possible that fewer than k clusters are created.
    --- End diff --
    
    If we back out change to avoid duplicate centroids, does this annotation be invalid?


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