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

    https://github.com/apache/spark/pull/16699#discussion_r100934554
  
    --- Diff: 
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
 ---
    @@ -798,77 +798,160 @@ class GeneralizedLinearRegressionSuite
         }
       }
     
    -  test("glm summary: gaussian family with weight") {
    +  test("generalized linear regression with offset") {
         /*
    -       R code:
    +      R code:
    +      library(statmod)
     
    -       A <- matrix(c(0, 1, 2, 3, 5, 7, 11, 13), 4, 2)
    -       b <- c(17, 19, 23, 29)
    -       w <- c(1, 2, 3, 4)
    -       df <- as.data.frame(cbind(A, b))
    -     */
    -    val datasetWithWeight = Seq(
    -      Instance(17.0, 1.0, Vectors.dense(0.0, 5.0).toSparse),
    -      Instance(19.0, 2.0, Vectors.dense(1.0, 7.0)),
    -      Instance(23.0, 3.0, Vectors.dense(2.0, 11.0)),
    -      Instance(29.0, 4.0, Vectors.dense(3.0, 13.0))
    +      df <- as.data.frame(matrix(c(
    +        0.2, 1.0, 2.0, 0.0, 5.0,
    +        0.5, 2.1, 0.5, 1.0, 2.0,
    +        0.9, 0.4, 1.0, 2.0, 1.0,
    +        0.7, 0.7, 0.0, 3.0, 3.0), 4, 5, byrow = TRUE))
    +      families <- list(gaussian, binomial, poisson, Gamma, tweedie(1.5))
    +      f1 <- V1 ~ -1 + V4 + V5
    +      f2 <- V1 ~ V4 + V5
    +      for (f in c(f1, f2)) {
    +        for (fam in families) {
    +          model <- glm(f, df, family = fam, weights = V2, offset = V3)
    +          print(as.vector(coef(model)))
    +        }
    +      }
    +      [1]  0.5169222 -0.3344444
    +      [1]  0.9419107 -0.6864404
    +      [1]  0.1812436 -0.6568422
    +      [1] -0.2869094  0.7857710
    +      [1] 0.1055254 0.2979113
    +      [1] -0.05990345  0.53188982 -0.32118415
    +      [1] -0.2147117  0.9911750 -0.6356096
    +      [1] -1.5616130  0.6646470 -0.3192581
    +      [1]  0.3390397 -0.3406099  0.6870259
    +      [1] 0.3665034 0.1039416 0.1484616
    +    */
    +    val dataset = Seq(
    +      OffsetInstance(0.2, 1.0, 2.0, Vectors.dense(0.0, 5.0)),
    +      OffsetInstance(0.5, 2.1, 0.5, Vectors.dense(1.0, 2.0)),
    +      OffsetInstance(0.9, 0.4, 1.0, Vectors.dense(2.0, 1.0)),
    +      OffsetInstance(0.7, 0.7, 0.0, Vectors.dense(3.0, 3.0))
         ).toDF()
    +
    +    val expected = Seq(
    +      Vectors.dense(0, 0.5169222, -0.3344444),
    +      Vectors.dense(0, 0.9419107, -0.6864404),
    +      Vectors.dense(0, 0.1812436, -0.6568422),
    +      Vectors.dense(0, -0.2869094, 0.785771),
    +      Vectors.dense(0, 0.1055254, 0.2979113),
    +      Vectors.dense(-0.05990345, 0.53188982, -0.32118415),
    +      Vectors.dense(-0.2147117, 0.991175, -0.6356096),
    +      Vectors.dense(-1.561613, 0.664647, -0.3192581),
    +      Vectors.dense(0.3390397, -0.3406099, 0.6870259),
    +      Vectors.dense(0.3665034, 0.1039416, 0.1484616))
    +
    +    import GeneralizedLinearRegression._
    +
    +    var idx = 0
    +
    +    for (fitIntercept <- Seq(false, true)) {
    +      for (family <- Seq("gaussian", "binomial", "poisson", "gamma", 
"tweedie")) {
    --- End diff --
    
    +1 this is a great idea


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