uros-b commented on code in PR #57206:
URL: https://github.com/apache/spark/pull/57206#discussion_r3587737747
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mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala:
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@@ -188,17 +193,19 @@ class GBTClassifier @Since("1.4.0") (
instr.logParams(this, labelCol, weightCol, featuresCol, predictionCol,
leafCol,
impurity, lossType, maxDepth, maxBins, maxIter, maxMemoryInMB,
minInfoGain,
minInstancesPerNode, minWeightFractionPerNode, seed, stepSize,
subsamplingRate, cacheNodeIds,
- checkpointInterval, featureSubsetStrategy, validationIndicatorCol,
validationTol, thresholds)
+ checkpointInterval, featureSubsetStrategy, validationIndicatorCol,
validationTol, thresholds,
+ intermediateStorageLevel)
instr.logNumClasses(numClasses)
val categoricalFeatures =
MetadataUtils.getCategoricalFeatures(dataset.schema($(featuresCol)))
val boostingStrategy = super.getOldBoostingStrategy(categoricalFeatures,
OldAlgo.Classification)
+ val storageLevel = StorageLevel.fromString($(intermediateStorageLevel))
Review Comment:
Minor style inconsistency: RandomForestClassifier/RandomForestRegressor
inline StorageLevel.fromString($(intermediateStorageLevel)) as a named arg,
while GBTClassifier/GBTRegressor extract a local val storageLevel. Harmonizing
these would be nicer.
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