Github user sethah commented on a diff in the pull request: https://github.com/apache/spark/pull/15394#discussion_r83084385 --- Diff: mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala --- @@ -132,24 +197,234 @@ class WeightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext var idx = 0 for (fitIntercept <- Seq(false, true)) { for (standardization <- Seq(false, true)) { - val wls = new WeightedLeastSquares( - fitIntercept, regParam = 0.0, standardizeFeatures = standardization, - standardizeLabel = standardization).fit(instancesConstLabel) - val actual = Vectors.dense(wls.intercept, wls.coefficients(0), wls.coefficients(1)) - assert(actual ~== expected(idx) absTol 1e-4) + for (solver <- WeightedLeastSquares.supportedSolvers) { + val wls = new WeightedLeastSquares(fitIntercept, regParam = 0.0, elasticNetParam = 0.0, + standardizeFeatures = standardization, + standardizeLabel = standardization, solverType = solver).fit(instancesConstLabel) + val actual = Vectors.dense(wls.intercept, wls.coefficients(0), wls.coefficients(1)) + assert(actual ~== expected(idx) absTol 1e-4) + } } idx += 1 } + + // when label is constant zero, and fitIntercept is false, we should not train and get all zeros + val instancesConstZeroLabel = instancesConstLabel.map { case Instance(l, w, f) => --- End diff -- done, moved them all
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