在这个 XGBoost 树中如何计算休假的分数? [英] How leave's scores are calculated in this XGBoost trees?

问题描述

我正在查看下图.

谁能解释一下它们是如何计算的?我虽然 N 为 -1，是的 +1，但后来我无法弄清楚这个小女孩是如何拥有 0.1 的.但这对树 2 也不起作用.

Can someone explain how they are calculated? I though it was -1 for an N and +1 for a yes but then I can't figure out how the little girl has .1. But that doesn't work for tree 2 either.

推荐答案

叶子元素的值(又名分数") - +2, +0.1, -1、+0.9 和 -0.9 - 是在训练期间由 XGBoost 算法设计的.在这种情况下，XGBoost 模型是使用数据集训练的，其中小男孩 (+2) 以某种方式看起来比小女孩 (+0.1)大".如果您知道响应变量是什么，那么您可能可以进一步解释/合理化这些贡献.否则，直接接受这些值.

The values of leaf elements (aka "scores") - +2, +0.1, -1, +0.9 and -0.9 - were devised by the XGBoost algorithm during training. In this case, the XGBoost model was trained using a dataset where little boys (+2) appear somehow "greater" than little girls (+0.1). If you knew what the response variable was, then you could probably interpret/rationalize those contributions further. Otherwise, just accept those values as they are.

对于打分样本，那么第一个加数由tree1产生，第二个加数由tree2产生.对于小男孩(年龄<15，是男性== Y，并且每天使用计算机== Y)，tree1 产生2 和 tree2 产生 0.9.

As for scoring samples, then the first addend is produced by tree1, and the second addend is produced by tree2. For little boys (age < 15, is male == Y, and use computer daily == Y), tree1 yields 2 and tree2 yields 0.9.

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