[jvm-packages] remove default parameters (#7938)

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoost.scala

@@ -166,7 +166,8 @@ private[this] class XGBoostExecutionParamsFactory(rawParams: Map[String, Any], s
   def buildXGBRuntimeParams: XGBoostExecutionParams = {
     val nWorkers = overridedParams("num_workers").asInstanceOf[Int]
     val round = overridedParams("num_round").asInstanceOf[Int]
-    val useExternalMemory = overridedParams("use_external_memory").asInstanceOf[Boolean]
+    val useExternalMemory = overridedParams
+      .getOrElse("use_external_memory", false).asInstanceOf[Boolean]
     val obj = overridedParams.getOrElse("custom_obj", null).asInstanceOf[ObjectiveTrait]
     val eval = overridedParams.getOrElse("custom_eval", null).asInstanceOf[EvalTrait]
     val missing = overridedParams.getOrElse("missing", Float.NaN).asInstanceOf[Float]

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/BoosterParams.scala

@@ -1,5 +1,5 @@
 /*
- Copyright (c) 2014,2021 by Contributors
+ Copyright (c) 2014-2022 by Contributors
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -261,6 +261,7 @@ private[spark] trait BoosterParams extends Params {
 
   final val treeLimit = new IntParam(this, name = "treeLimit",
     doc = "number of trees used in the prediction; defaults to 0 (use all trees).")
+  setDefault(treeLimit, 0)
 
   final def getTreeLimit: Int = $(treeLimit)
 
@@ -280,13 +281,6 @@ private[spark] trait BoosterParams extends Params {
 
   final def getInteractionConstraints: String = $(interactionConstraints)
 
-  setDefault(eta -> 0.3, gamma -> 0, maxDepth -> 6,
-    minChildWeight -> 1, maxDeltaStep -> 0,
-    growPolicy -> "depthwise", maxBins -> 256,
-    subsample -> 1, colsampleBytree -> 1, colsampleBylevel -> 1,
-    lambda -> 1, alpha -> 0, treeMethod -> "auto", sketchEps -> 0.03,
-    scalePosWeight -> 1.0, sampleType -> "uniform", normalizeType -> "tree",
-    rateDrop -> 0.0, skipDrop -> 0.0, lambdaBias -> 0, treeLimit -> 0)
 }
 
 private[scala] object BoosterParams {

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/GeneralParams.scala

@@ -29,6 +29,7 @@ private[spark] trait GeneralParams extends Params {
    */
   final val numRound = new IntParam(this, "numRound", "The number of rounds for boosting",
     ParamValidators.gtEq(1))
+  setDefault(numRound, 1)
 
   final def getNumRound: Int = $(numRound)
 
@@ -37,6 +38,7 @@ private[spark] trait GeneralParams extends Params {
    */
   final val numWorkers = new IntParam(this, "numWorkers", "number of workers used to run xgboost",
     ParamValidators.gtEq(1))
+  setDefault(numWorkers, 1)
 
   final def getNumWorkers: Int = $(numWorkers)
 
@@ -45,6 +47,7 @@ private[spark] trait GeneralParams extends Params {
    */
   final val nthread = new IntParam(this, "nthread", "number of threads used by per worker",
     ParamValidators.gtEq(1))
+  setDefault(nthread, 1)
 
   final def getNthread: Int = $(nthread)
 
@@ -53,6 +56,7 @@ private[spark] trait GeneralParams extends Params {
    */
   final val useExternalMemory = new BooleanParam(this, "useExternalMemory",
     "whether to use external memory as cache")
+  setDefault(useExternalMemory, false)
 
   final def getUseExternalMemory: Boolean = $(useExternalMemory)
 
@@ -94,6 +98,7 @@ private[spark] trait GeneralParams extends Params {
    * the value treated as missing. default: Float.NaN
    */
   final val missing = new FloatParam(this, "missing", "the value treated as missing")
+  setDefault(missing, Float.NaN)
 
   final def getMissing: Float = $(missing)
 
@@ -109,6 +114,7 @@ private[spark] trait GeneralParams extends Params {
       "not use Spark's VectorAssembler class to construct the feature vector " +
       "but instead used a method that preserves zeros in your vector."
   )
+  setDefault(allowNonZeroForMissing, false)
 
   final def getAllowNonZeroForMissingValue: Boolean = $(allowNonZeroForMissing)
 
@@ -163,18 +169,14 @@ private[spark] trait GeneralParams extends Params {
     *        Ignored if the tracker implementation is "python".
     */
   final val trackerConf = new TrackerConfParam(this, "trackerConf", "Rabit tracker configurations")
+  setDefault(trackerConf, TrackerConf())
 
   /** Random seed for the C++ part of XGBoost and train/test splitting. */
   final val seed = new LongParam(this, "seed", "random seed")
+  setDefault(seed, 0L)
 
   final def getSeed: Long = $(seed)
 
-  setDefault(numRound -> 1, numWorkers -> 1, nthread -> 1,
-    useExternalMemory -> false, silent -> 0, verbosity -> 1,
-    customObj -> null, customEval -> null, missing -> Float.NaN,
-    trackerConf -> TrackerConf(), seed -> 0,
-    checkpointPath -> "", checkpointInterval -> -1,
-    allowNonZeroForMissing -> false)
 }
 
 trait HasLeafPredictionCol extends Params {

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/InferenceParams.scala

@@ -1,5 +1,5 @@
 /*
- Copyright (c) 2014 by Contributors
+ Copyright (c) 2014-2022 by Contributors
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -26,7 +26,7 @@ private[spark] trait InferenceParams extends Params {
   final val inferBatchSize = new IntParam(this, "batchSize", "batch size of inference iteration")
 
   /** @group getParam */
-  final def getInferBatchSize: Int = ${inferBatchSize}
+  final def getInferBatchSize: Int = $(inferBatchSize)
 
   setDefault(inferBatchSize, 32 << 10)
 }

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/LearningTaskParams.scala

@@ -71,6 +71,7 @@ private[spark] trait LearningTaskParams extends Params {
   final val trainTestRatio = new DoubleParam(this, "trainTestRatio",
     "fraction of training points to use for testing",
     ParamValidators.inRange(0, 1))
+  setDefault(trainTestRatio, 1.0)
 
   final def getTrainTestRatio: Double = $(trainTestRatio)
 
@@ -105,8 +106,6 @@ private[spark] trait LearningTaskParams extends Params {
 
   final def getMaximizeEvaluationMetrics: Boolean = $(maximizeEvaluationMetrics)
 
-  setDefault(baseScore -> 0.5, trainTestRatio -> 1.0,
-    numEarlyStoppingRounds -> 0, cacheTrainingSet -> false)
 }
 
 private[spark] object LearningTaskParams {

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/RabitParams.scala

@@ -1,5 +1,5 @@
 /*
- Copyright (c) 2014 by Contributors
+ Copyright (c) 2014-2022 by Contributors
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -29,12 +29,14 @@ private[spark] trait RabitParams extends Params {
   final val rabitRingReduceThreshold = new IntParam(this, "rabitRingReduceThreshold",
     "threshold count to enable allreduce/broadcast with ring based topology",
           ParamValidators.gtEq(1))
+  setDefault(rabitRingReduceThreshold, (32 << 10))
 
   final def rabitTimeout: IntParam = new IntParam(this, "rabitTimeout",
   "timeout threshold after rabit observed failures")
+  setDefault(rabitTimeout, -1)
 
   final def rabitConnectRetry: IntParam = new IntParam(this, "dmlcWorkerConnectRetry",
     "number of retry worker do before fail", ParamValidators.gtEq(1))
+  setDefault(rabitConnectRetry, 5)
 
-  setDefault(rabitRingReduceThreshold -> (32 << 10), rabitConnectRetry -> 5, rabitTimeout -> -1)
 }

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/XGBoostEstimatorCommon.scala

@@ -29,7 +29,8 @@ private[scala] sealed trait XGBoostEstimatorCommon extends GeneralParams with Le
   with HasLabelCol with HasFeaturesCols with HasHandleInvalid {
 
   def needDeterministicRepartitioning: Boolean = {
-    getCheckpointPath != null && getCheckpointPath.nonEmpty && getCheckpointInterval > 0
+    isDefined(checkpointPath) && getCheckpointPath != null && getCheckpointPath.nonEmpty &&
+      isDefined(checkpointInterval) && getCheckpointInterval > 0
   }
 
   /**

jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/ParameterSuite.scala

@@ -84,4 +84,11 @@ class ParameterSuite extends FunSuite with PerTest with BeforeAndAfterAll {
 
     new XGBoostClassifier(paramMap).fit(trainingDF)
   }
+
+  test("Default parameters") {
+    val classifier = new XGBoostClassifier()
+    intercept[NoSuchElementException] {
+      classifier.getBaseScore
+    }
+  }
 }