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From dbtsai <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-11207][ML] Add test cases for solver se...
Date Thu, 29 Oct 2015 17:29:11 GMT
Github user dbtsai commented on a diff in the pull request:

    https://github.com/apache/spark/pull/9180#discussion_r43417193
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala ---
    @@ -104,7 +103,35 @@ object LinearDataGenerator {
           nPoints: Int,
           seed: Int,
           eps: Double): Seq[LabeledPoint] = {
    +    generateLinearInputInternal(intercept, weights, xMean, xVariance, nPoints, seed,
eps, 0.0)
    +  }
     
    +
    +  /**
    +   * @param intercept Data intercept
    +   * @param weights  Weights to be applied.
    +   * @param xMean the mean of the generated features. Lots of time, if the features are
not properly
    +   *              standardized, the algorithm with poor implementation will have difficulty
    +   *              to converge.
    +   * @param xVariance the variance of the generated features.
    +   * @param nPoints Number of points in sample.
    +   * @param seed Random seed
    +   * @param eps Epsilon scaling factor.
    +   * @param sparcity The ratio of zero elements. If it is 0.0, LabeledPoints with
    +   *                 DenseVector is returned.
    +   * @return Seq of input.
    +   */
    +  @Since("1.6.0")
    +  def generateLinearInputInternal(
    --- End diff --
    
    Just call it `generateLinearInput` without `Internal`.


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