[GitHub] spark pull request #16630: [SPARK-19270][ML] Add summary table to GLM summar...

[imatiach-msft <gi...@git.apache.org>]

Github user imatiach-msft commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16630#discussion_r100927396
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala ---
    @@ -1152,4 +1170,32 @@ class GeneralizedLinearRegressionTrainingSummary private[regression] (
             "No p-value available for this GeneralizedLinearRegressionModel")
         }
       }
    +
    +  /**
    +   * Summary table with feature name, coefficient, standard error,
    +   * tValue and pValue.
    +   */
    +  @Since("2.2.0")
    +  lazy val summaryTable: DataFrame = {
    +    if (isNormalSolver) {
    +      var featureNames = featureName
    +      var coefficients = model.coefficients.toArray
    +      var idx = Array.range(0, coefficients.length)
    +      if (model.getFitIntercept) {
    +        featureNames = featureNames :+ "Intercept"
    +        coefficients = coefficients :+ model.intercept
    +        // Reorder so that intercept comes first
    +        idx = (coefficients.length - 1) +: idx
    +      }
    +      val result = for (i <- idx.toSeq) yield
    +        (featureNames(i), coefficients(i), coefficientStandardErrors(i), tValues(i), pValues(i))
    +
    +      val spark = SparkSession.builder().getOrCreate()
    +      import spark.implicits._
    --- End diff --
    
    minor comment: might it be better to simplify this as "import dataset.sparkSession.implicits._", or is there a reason to prefer the SparkSession.builder().getOrCreate()?


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