构建 Rpart 数据树错误类型无效（列表）答案

【问题标题】：Building Rpart Data Tree Error Invalid Type(list)构建 Rpart 数据树错误类型无效（列表）
【发布时间】：2021-02-14 10:09:09
【问题描述】：

我是编码新手，我正在尝试构建数据树，但我一直遇到同样的错误：

错误 model.frame.default(公式 = df ~ df$Open.Closed + df$Region, : 变量“df”的类型（列表）无效

我浏览了整个网站，但未能找到解决问题的有效方法。我尝试了多种解决方案，但我通常会遇到另一个错误，即数据是矩阵，该部分不会接受。任何帮助将不胜感激。

这是我的代码：

library(rpart.plot)
library(ggExtra)
library(gridExtra)
library(RGtk2)
library(rpart)
library(rattle)
df[] <- data.frame(lapply(Test_Bank_Model,factor))
df [col_names] <- lapply(df[col_names], factor)

str(df)
summary(df)
print(df)


tree <- rpart(df ~ df$Open.Closed + df$Region, data = df, method = "class",
          model = TRUE, control = rpart.control("minsplit" = 1))
rpart.plot(tree, roundint = FALSE, box.palette = "white")

Data:
Region
Closing.Date
Annual.Average.FedFunds
Open.Closed
1   South   2020    0.2328571   Closed
2   Mid West    2020    0.2328571   Closed
3   North East  2020    0.2328571   Open
4   South   2020    0.2328571   Open
5   North East  2020    0.2328571   Open
6   West    2020    0.2328571   Open
7   North East  2020    0.2328571   Open
8   North East  2019    1.7366667   Closed
9   South   2019    1.7366667   Closed
10  Mid West    2019    1.7366667   Closed

【问题讨论】：

标签： r tree gridextra rpart rattle

【解决方案1】：

根据错误消息，我认为您在需要数据框时正在使用列表对象。

lapply 以列表形式返回结果。我认为这就是格式变化被忽视的地方。

我创建了一个名为“Test_Bank_Model”的数据框，获取了列名并排除了“Annual.Average.FedFunds”转换为因子（我不确定你想用这些年做什么）。

在rpart 中，您可以像以前一样通过 data 参数指定 data.frame。当你这样做时，你可以省去自己重新输入数据框名称（但我不知道这是有问题的；它也应该可以工作）。

Test_Bank_Model <- data.frame(Region = c("South","Mid West","North East","South","North East","West","North East","North East","South"),
    Closing.Date = c(rep(2020,7), 2019,2019),
    Annual.Average.FedFunds = c(0.2328571,0.2328571,0.2328571,0.2328571,0.2328571,0.2328571,0.2328571,1.7366667,1.7366667),
    Open.Closed = c("Closed","Closed","Open","Open","Open","Open","Open","Closed","Closed"))

col_names <- colnames(Test_Bank_Model)[-3]

Test_Bank_Model[,col_names] <- as.data.frame(lapply(Test_Bank_Model[,col_names], FUN=as.factor))

str(Test_Bank_Model)
# 'data.frame': 9 obs. of  4 variables:
#  $ Region                 : Factor w/ 4 levels "Mid West","North East",..: 3 1 2 3 2 4 2 2 3
#  $ Closing.Date           : Factor w/ 2 levels "2019","2020": 2 2 2 2 2 2 2 1 1
#  $ Annual.Average.FedFunds: num  0.233 0.233 0.233 0.233 0.233 ...
#  $ Open.Closed            : Factor w/ 2 levels "Closed","Open": 1 1 2 2 2 2 2 1 1

tree <- rpart(Annual.Average.FedFunds ~ Open.Closed + Region,
    data = Test_Bank_Model,
    method = "class",
    model = TRUE,
    control = rpart.control("minsplit" = 1))
rpart.plot(tree, roundint = FALSE, box.palette = "white")

【讨论】：