Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/17034#discussion_r103853075
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
---
@@ -361,6 +363,36 @@ class AFTSurvivalRegressionSuite
}
}
+ test("should support all NumericType censors, and not support other
types") {
+ val df = spark.createDataFrame(Seq(
+ (0, Vectors.dense(0)),
+ (1, Vectors.dense(1)),
+ (2, Vectors.dense(2)),
+ (3, Vectors.dense(3)),
+ (4, Vectors.dense(4))
+ )).toDF("label", "features")
+ .withColumn("censor", lit(0.0))
+ val aft = new AFTSurvivalRegression().setMaxIter(1)
+ val expected = aft.fit(df)
+
+ val types = Seq(ShortType, LongType, IntegerType, FloatType, ByteType,
DecimalType(10, 0))
+ types.foreach { t =>
+ val actual = aft.fit(df.select(col("label"), col("features"),
+ col("censor").cast(t)))
+ assert(expected.intercept === actual.intercept)
+ assert(expected.coefficients === actual.coefficients)
+ }
+
+ val dfWithStringCensors = spark.createDataFrame(Seq(
+ (0, Vectors.dense(0, 2, 3), "0")
+ )).toDF("label", "features", "censor")
+ val thrown = intercept[IllegalArgumentException] {
--- End diff --
can you wrap this in a withClue("Column censor must be of type NumericType
but was actually of type StringType") {
...
}
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