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[jvm-packages] Accept groupData in spark model eval (#2244)

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* Support model evaluation for ranking tasks by accepting
 groupData in XGBoostModel.eval
This commit is contained in:
ebernhardson
2017-05-02 10:03:20 -07:00
committed by Nan Zhu
parent a375ad2822
commit ccccf8a015
2 changed files with 11 additions and 2 deletions
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5
jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostGeneralSuite.scala
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@@ -352,12 +352,15 @@ class XGBoostGeneralSuite extends SharedSparkContext with Utils {
val testRDD = sc.parallelize(testSet, numSlices = 1).map(_.features)
val paramMap = Map("eta" -> "1", "max_depth" -> "6", "silent" -> "1",
"objective" -> "rank:pairwise", "groupData" -> trainGroupData)
"objective" -> "rank:pairwise", "eval_metric" -> "ndcg", "groupData" -> trainGroupData)
val xgBoostModel = XGBoost.trainWithRDD(trainingRDD, paramMap, 5, nWorkers = 1)
val predRDD = xgBoostModel.predict(testRDD)
val predResult1: Array[Array[Float]] = predRDD.collect()(0)
assert(testRDD.count() === predResult1.length)
val avgMetric = xgBoostModel.eval(trainingRDD, "test", iter = 0, groupData = trainGroupData)
assert(avgMetric contains "ndcg")
}
test("test use nested groupData") {