Github user feynmanliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7099#discussion_r33984405
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
---
@@ -87,6 +86,42 @@ class LinearRegressionSuite extends SparkFunSuite with
MLlibTestSparkContext {
features(0) * model.weights(0) + features(1) * model.weights(1)
+ model.intercept
assert(prediction1 ~== prediction2 relTol 1E-5)
}
+
+ // Training results for the model should be available
+ assert(model.getTrainingResults.isDefined)
+
+ // Residuals in [[LinearRegressionResults]] should equal those
manually computed
+ dataset.select("features", "label").map {
+ case Row(features: DenseVector, label: Double) =>
+ val prediction =
+ features(0) * model.weights(0) + features(1) * model.weights(1)
+ model.intercept
+ prediction - label
+ }.zip(model.getTrainingResults.get.residuals.map(_.getDouble(0)))
+ .collect()
+ .foreach {
+ case (manualResidual: Double, resultResidual: Double) =>
--- End diff --
Which comparison can be used for elementwise approximate equals with
tolerance (I'm comparing two `Array[Double]`s)? I saw
`IndexSeqOptimized#sameElements` but that tests for exact equality (`==`) and
`TestingUtils` seems to only have stuff for `Vectors`.
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