Github user MLnick commented on a diff in the pull request: https://github.com/apache/spark/pull/15149#discussion_r79556533 --- Diff: mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala --- @@ -56,6 +56,21 @@ class ProbabilisticClassifierSuite extends SparkFunSuite { val testModel = new TestProbabilisticClassificationModel("myuid", 2, 2) assert(testModel.friendlyPredict(Vectors.dense(Array(1.0, 2.0))) === 1.0) } + + test("test tiebreak") { + val testModel = new TestProbabilisticClassificationModel("myuid", 2, 2) + .setThresholds(Array(0.4, 0.4)) + assert(testModel.friendlyPredict(Vectors.dense(Array(0.6, 0.6))) === 0.0) + } + + test("bad thresholds") { + intercept[IllegalArgumentException] { --- End diff -- No they don't seem to be probabilities. In fact I don't see a theoretical reason why the sum <=1, since they're just scalings or "weights". Requiring all > 0 of course makes practical sense. Anyway we should just match what they do as that is what this `thresholds` implementation was based on.
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