Github user sethah commented on a diff in the pull request: https://github.com/apache/spark/pull/15683#discussion_r87609107 --- Diff: mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala --- @@ -453,6 +464,56 @@ class GeneralizedLinearRegressionSuite } } + test("generalized linear regression: poisson family against glm (with zero values)") { + /* + R code: + f1 <- data$V1 ~ data$V2 + data$V3 - 1 + f2 <- data$V1 ~ data$V2 + data$V3 + + data <- read.csv("path", header=FALSE) + for (formula in c(f1, f2)) { + model <- glm(formula, family="poisson", data=data) + print(as.vector(coef(model))) + } + [1] 0.4272661 -0.1565423 + [1] -3.6911354 0.6214301 0.1295814 + + */ + val expected = Seq( + Vectors.dense(0.0, 0.4272661, -0.1565423), + Vectors.dense(-3.6911354, 0.6214301, 0.1295814)) + + import GeneralizedLinearRegression._ + + var idx = 0 + val link = "log" + val dataset = datasetPoissonLogWithZero + for (fitIntercept <- Seq(false, true)) { + val trainer = new GeneralizedLinearRegression().setFamily("poisson").setLink(link) + .setFitIntercept(fitIntercept).setLinkPredictionCol("linkPrediction") + val model = trainer.fit(dataset) + val actual = Vectors.dense(model.intercept, model.coefficients(0), model.coefficients(1)) + assert(actual ~= expected(idx) absTol 1e-4, "Model mismatch: GLM with poisson family, " + + s"$link link and fitIntercept = $fitIntercept (with zero values).") + + val familyLink = new FamilyAndLink(Poisson, Link.fromName(link)) + model.transform(dataset).select("features", "prediction", "linkPrediction").collect() --- End diff -- I don't see any reason to test the predictions here. Checking the coefficients should be enough, since we test for correctness in other places.
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