提取与新观测值关联的每棵树的终端节点 [英] Extracting the terminal nodes of each tree associated with a new observation

问题描述

我想提取随机森林R实现的终端节点.据我所知，随机森林中有一系列正交树.当您预测一个新的观测值(回归)时，它会进入所有这些树，然后平均每个树的预测值.如果我不希望取平均，而是可能对这些相应的观察值进行线性回归，则需要一个与该新观察值相关"的观察值列表.我已经看完了源代码，但还没有想出一种方法来获得它.谁能帮我吗?

I would like to extract the terminal nodes of the random forest R implementation. As I have understood random forest, you have a sequence of orthogonal trees. When you predict a new observation (In regression), it enters all these trees and then you average the prediction of each individual tree. If I wanted to not average but maybe do a linear regression with these corresponding observations I would need, say, a list of the observations that are "associated" with this new observation. I have gone through the source code but havent come up with a way to obtain this. Can anyone help me?

推荐答案

必须有更好的方法，但这是一种解决方法:

There must be a better way to do this, but here's a workaround:

library(randomForest)
set.seed(713)
## data
my.df <- data.frame(x = rnorm(100), y = rnorm(100))
## forest
rf <- randomForest(y ~ x, data = my.df, ntree = 10, keep.inbag = TRUE)

keep.inbag = TRUE保存该示例中用于容纳10棵树中的每一个的袋内观察值

keep.inbag = TRUE saves the inbag observations that are used to fit each of the 10 trees in this example

predList <- lapply(seq_len(rf$ntree), function(z) 
            predict(rf, newdata = my.df[rf$inbag[, z] == 1, ], nodes = TRUE))

nodes = TRUE跟踪每个观察结束的终端节点.

nodes = TRUE tracks the terminal nodes each observation ends in.

node.list <- lapply(seq_len(rf$ntree), function(z) 
            split(x = my.df[rf$inbag[, z] == 1, "x"], 
                    f = attr(predList[[z]], "nodes")[, z]))

第一棵树的前三个终端节点:

First three terminal nodes of the first tree:

node.list[[1]][1:3]

$`3`
[1] 2.028358 2.071939

$`7`
[1] 0.8306559

$`9`
[1] 1.660134 1.621299

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