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[jvm-packages] Fix "obj_type" error to enable custom objectives and evaluations (#3646)

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credits to @mmui
This commit is contained in:
Michael Mui
2018-09-14 12:06:33 -07:00
committed by Nan Zhu
parent 7bbb44182a
commit 20a9e716bd
5 changed files with 33 additions and 4 deletions
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5
jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifierSuite.scala
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@@ -140,15 +140,18 @@ class XGBoostClassifierSuite extends FunSuite with PerTest {
}
test("XGBoost and Spark parameters synchronize correctly") {
val xgbParamMap = Map("eta" -> "1", "objective" -> "binary:logistic")
val xgbParamMap = Map("eta" -> "1", "objective" -> "binary:logistic",
"objective_type" -> "classification")
// from xgboost params to spark params
val xgb = new XGBoostClassifier(xgbParamMap)
assert(xgb.getEta === 1.0)
assert(xgb.getObjective === "binary:logistic")
assert(xgb.getObjectiveType === "classification")
// from spark to xgboost params
val xgbCopy = xgb.copy(ParamMap.empty)
assert(xgbCopy.MLlib2XGBoostParams("eta").toString.toDouble === 1.0)
assert(xgbCopy.MLlib2XGBoostParams("objective").toString === "binary:logistic")
assert(xgbCopy.MLlib2XGBoostParams("objective_type").toString === "classification")
val xgbCopy2 = xgb.copy(ParamMap.empty.put(xgb.evalMetric, "logloss"))
assert(xgbCopy2.MLlib2XGBoostParams("eval_metric").toString === "logloss")
}