def getLeafNodes(node:Node):Array[Int] = {
    var treeLeafNodes = new Array[Int](0)
    if (node.isLeaf){
      treeLeafNodes = treeLeafNodes.:+(node.id)
    }else{
      treeLeafNodes = treeLeafNodes ++ getLeafNodes(node.leftNode.get)
      treeLeafNodes = treeLeafNodes ++ getLeafNodes(node.rightNode.get)
    }
    treeLeafNodes
  }


val numTrees = 100
    val boostingStrategy = BoostingStrategy.defaultParams("Classification")
    boostingStrategy.numIterations = 100 // Note: Use more iterations in practice.
    boostingStrategy.treeStrategy.numClasses = 2
    boostingStrategy.treeStrategy.maxDepth = 4
    boostingStrategy.learningRate = 0.01
    // Empty categoricalFeaturesInfo indicates all features are continuous.
    boostingStrategy.treeStrategy.categoricalFeaturesInfo = Map[Int, Int]()

    val gbdtModel = GradientBoostedTrees.train(data, boostingStrategy)

    println("gbdt train ok")
//    print(gbdtModel.toDebugString)


    //根据gbdt模型，拿到叶子节点特征
    val treeLeafArray = new Array[Array[Int]](numTrees)
    for(i<- 0.until(numTrees)){
      treeLeafArray(i) = getLeafNodes(gbdtModel.trees(i).topNode)
    }