Clarify Bucketizer handling of invalid input

contDF = spark.range(500).selectExpr("cast(id as double) as id")
import org.apache.spark.ml.feature.Bucketizer

val splits = Array(5.0, 10.0, 250.0, 500.0)

val bucketer = new Bucketizer()
  .setSplits(splits)
  .setInputCol("id")
  .setHandleInvalid("skip")

bucketer.transform(contDF).show()

Caused by: org.apache.spark.SparkException: Feature value 0.0 out of Bucketizer bounds [5.0, 500.0].  Check your features, or loosen the lower/upper bound constraints.