在下面的xgboost模型树图中，"leaf"的值是什么意思? [英] What does the value of 'leaf' in the following xgboost model tree diagram means?

问题描述

我猜想这是有条件的概率，因为存在上述(树分支)条件.但是，我不清楚.

I am guessing that it is conditional probability given that the above (tree branch) condition exists. However, I am not clear on it.

如果您想了解有关使用的数据的更多信息或如何获得此图，请访问:

If you want to read more about the data used or how do we get this diagram then go to : http://machinelearningmastery.com/visualize-gradient-boosting-decision-trees-xgboost-python/

推荐答案

属性leaf是预测值.换句话说，如果对树模型的评估在该终端节点(也称为叶节点)处结束，那么这就是返回的值.

Attribute leaf is the predicted value. In other words, if the evaluation of a tree model ends at that terminal node (aka leaf node), then this is the value that is returned.

使用伪代码(树模型的最左侧分支):

In pseudocode (the left-most branch of your tree model):

if(f1 < 127.5){
  if(f7 < 28.5){
    if(f5 < 45.4){
      return 0.167528f;
    } else {
      return 0.05f;
    }
  }
}

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