Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8836#discussion_r40126117
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
---
@@ -302,7 +320,44 @@ class AFTSurvivalRegressionSuite extends SparkFunSuite
with MLlibTestSparkContex
model.setQuantileProbabilities(quantileProbabilities)
assert(model.predictQuantiles(features) ~== quantilePredictR relTol
1E-3)
- model.transform(datasetMultivariate).select("features",
"prediction").collect().foreach {
+ model.setQuantilesCol("quantiles")
+ model.transform(datasetMultivariate).select("features", "prediction",
"quantiles")
+ .collect().foreach {
+ case Row(features: DenseVector, prediction1: Double,
predictionQuantiles1: Vector) =>
+ val lambda = math.exp(BLAS.dot(model.coefficients, features) +
model.intercept)
+ val k = 1 / model.scale
+ val prediction2 = lambda
+ val predictionQuantiles2 =
Vectors.dense(model.getQuantileProbabilities.map {
+ q => lambda * math.exp(math.log(-math.log(1 - q)) / k)
+ })
+ assert(prediction1 ~== prediction2 relTol 1E-5)
+ assert(predictionQuantiles1 ~== predictionQuantiles2 relTol 1E-5)
+ }
+ }
+
+ test("aft survival regression w/o quantiles column") {
+ val trainer = new AFTSurvivalRegression
+
+ val features = Vectors.dense(6.559282795753792)
+ val quantileProbabilities = Array(0.1, 0.5, 0.9)
+ val quantilePredict = Vectors.dense(0.1879174, 2.6801195, 14.5779394)
+
+ val model = trainer.fit(datasetUnivariate)
+
+ intercept[IllegalArgumentException] {
--- End diff --
We need to update this test after we put a default value for
`quantileProbabilities` and update its validator.
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