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R:如何解释我方 plot 决策树?

[英]R: How to interpret my party plot decision tree?

I made a decision tree with party plot in R but don't really know what it's telling me.我在 R 中与派对 plot 制作了一个决策树,但我真的不知道它在告诉我什么。 The data is about the indian startup ecosystem.这些数据是关于印度创业生态系统的。 I don't know what nodes mean.我不知道节点是什么意思。

The tree displays the subsets found through recursive partitioning.树显示通过递归分区找到的子集。 The dependent variable in every resulting subset is visualized by a box plot.每个结果子集中的因变量由框 plot 可视化。

As an example, consider node 10:例如,考虑节点 10:

  • There are 95 observations in this subset.该子集中有 95 个观测值。
  • These are all the observations which used "seed funding" as the InvestmantnType and had a Date.dd.mm.yyyy in 15, 2018, or 2019.这些都是使用“种子资金”作为InvestmantnType在 2018 年 15 月或 2019 年具有Date.dd.mm.yyyy的所有观察结果。
  • The boxplot shows the distribution of the dependent variable Amount.in.USD for these 95 observations.箱线图显示了这 95 个观察值的因变量Amount.in.USD的分布。

You can extract the variable importance from tree$variable.importance or you can simply summary(tree) .您可以从tree$variable.importance中提取变量重要性,或者您可以简单地summary(tree) Variable importance tells us which variables are most important for the models to make decisions.变量重要性告诉我们哪些变量对模型做出决策最重要。

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