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[SPARK-9722][ML] Pass random seed to spark.ml DecisionTree* #9402

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[SPARK-9722][ML] Pass random seed to spark.ml DecisionTree* #9402

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8 changes: 5 additions & 3 deletions mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ private[ml] object RandomForest extends Logging {
// Find the splits and the corresponding bins (interval between the splits) using a sample
// of the input data.
timer.start("findSplitsBins")
val splits = findSplits(retaggedInput, metadata)
val splits = findSplits(retaggedInput, metadata, seed)
timer.stop("findSplitsBins")
logDebug("numBins: feature: number of bins")
logDebug(Range(0, metadata.numFeatures).map { featureIndex =>
Expand Down Expand Up @@ -815,6 +815,7 @@ private[ml] object RandomForest extends Logging {
*
* @param input Training data: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]]
* @param metadata Learning and dataset metadata
* @param seed random seed
* @return A tuple of (splits, bins).
* Splits is an Array of [[org.apache.spark.mllib.tree.model.Split]]
* of size (numFeatures, numSplits).
Expand All @@ -823,7 +824,8 @@ private[ml] object RandomForest extends Logging {
*/
protected[tree] def findSplits(
input: RDD[LabeledPoint],
metadata: DecisionTreeMetadata): Array[Array[Split]] = {
metadata: DecisionTreeMetadata,
seed : Long): Array[Array[Split]] = {

logDebug("isMulticlass = " + metadata.isMulticlass)

Expand All @@ -840,7 +842,7 @@ private[ml] object RandomForest extends Logging {
1.0
}
logDebug("fraction of data used for calculating quantiles = " + fraction)
input.sample(withReplacement = false, fraction, new XORShiftRandom(1).nextInt()).collect()
input.sample(withReplacement = false, fraction, new XORShiftRandom(seed).nextInt()).collect()
} else {
new Array[LabeledPoint](0)
}
Expand Down