Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/16740#discussion_r99276472
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -743,6 +744,48 @@ class GeneralizedLinearRegressionSuite
}
}
+ test("generalized linear regression: intercept only") {
+ /*
+ R code:
+ y <- c(17, 19, 23, 29)
+ w <- c(1, 2, 3, 4)
+ model1 <- glm(y ~ 1, family = poisson)
+ model2 <- glm(y ~ 1, family = poisson, weights = w)
+ as.vector(c(coef(model1), coef(model2)))
+ [1] 3.091042 3.178054
+ */
+
+ val dataset = Seq(
+ Instance(17.0, 1.0, Vectors.zeros(0)),
+ Instance(19.0, 2.0, Vectors.zeros(0)),
+ Instance(23.0, 3.0, Vectors.zeros(0)),
+ Instance(29.0, 4.0, Vectors.zeros(0))
+ ).toDF()
+
+ val expected = Seq(3.091, 3.178)
+
+ import GeneralizedLinearRegression._
+
+ var idx = 0
+ for (useWeight <- Seq(false, true)) {
+ val trainer = new GeneralizedLinearRegression().setFamily("poisson")
+ if (useWeight) trainer.setWeightCol("weight")
+ val model = trainer.fit(dataset)
+ val actual = model.intercept
+ assert(actual ~== expected(idx) absTol 1E-3, "Model mismatch:
intercept only GLM with " +
+ s"useWeight = $useWeight.")
+ assert(model.coefficients === new DenseVector(Array.empty[Double]))
+
+ idx += 1
+ }
+
+ // throw exception for empty model
+ val trainer = new GeneralizedLinearRegression().setFitIntercept(false)
+ intercept[SparkException] {
--- End diff --
thank you for adding the test, could you also please wrap it in withClue to
verify the message contents, eg:
withClue("Specified model is empty with neither intercept nor feature") {
intercept[SparkException] {
trainer.fit(dataset)
}
}
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