如何在添加多个列的“扩展转换（R 语法）”节点中正确制作“modelerData”和“modelerDataModel”

Question

我使用 SPSS 建模器 v18.2.1 和 R v3.5.1（或 v3.3.3）使用 Essentials for R 18.2.1。

我正在尝试制作“扩展转换（R 语法）”节点来处理 SPSS 难以处理的一些问题（未来：使它们成为扩展包）。我希望他们添加多个列，创建新数据等并给出下一个节点data.frame。但是data.frameSPSS 节点错误地识别了它们（即，下一个表节点的输出与 的控制台输出不同print(modelerData)）。
怎么做 ？（或者这是一个错误？）

任何帮助将不胜感激。下面是一个可重现的简单示例；

[准备R env和数据（请用纯R做）]

# if not installed 
install.packages(randomForest)

set.seed(1)  # to reproduce
write.csv(iris[sort(sample(1:150, 100)), ], "iris_train_seed1.csv", row.names = FALSE)

【我的节点流程】

【扩展变换的R代码】

### library ###
library(randomForest)

# make_model
set.seed(1)
modelerModel <- randomForest(formula = Species ~ . ,
                             data = modelerData,
                             ntree = 100)

#### predict
pred_forest <- data.frame(pred = predict(modelerModel, 
                                         newdata = modelerData))
prob_forest <- as.data.frame(predict(modelerModel, 
                                     newdata = modelerData,
                                     type = "prob"))


# overwriting modelerData
modelerData <- cbind(modelerData, pred_forest, prob_forest)

# function definition to make modelerDataModel 
getMetaData <- function (data) {
  if (dim(data)[1]<=0) {
    print("Warning : modelerData has no line, all fieldStorage fields set to strings")
    getStorage <- function(x){return("string")}
  } else {
    getStorage <- function(x) {
      res <- NULL
      #if x is a factor, typeof will return an integer so we treat the case on the side
      if(is.factor(x)) {
        res <- "string"
      } else {
        res <- switch(typeof(unlist(x)),
                      integer = "integer",
                      #  integer = "real",      
                      double = "real",
                      character = "string",
                      "string")
      }
      return (res)
    }
  }
  col = vector("list", dim(data)[2])
  for (i in 1:dim(data)[2]) {
    col[[i]] <- c(fieldName=names(data[i]),
                  fieldLabel="",
                  fieldStorage=getStorage(data[[i]]), 
                  fieldMeasure="",
                  fieldFormat="",
                  fieldRole="")
  }
  mdm<-do.call(cbind,col)
  mdm<-data.frame(mdm)
  return(mdm)
}

# overwriting modelerDataModel
modelerDataModel <- getMetaData(modelerData)

# to check
print(dim(modelerData))
print(head(modelerData))
print(dim(modelerDataModel))
print(modelerDataModel)

[“要检查”部分的控制台输出（print(modelerData)是我想要的表节点输出）]

# print(dim(modelerData))
[1] 100   9

# print(head(modelerData))
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species   pred setosa
1          4.9         3.0          1.4         0.2  setosa setosa      1
2          4.7         3.2          1.3         0.2  setosa setosa      1
3          5.0         3.6          1.4         0.2  setosa setosa      1
4          5.4         3.9          1.7         0.4  setosa setosa      1
5          4.6         3.4          1.4         0.3  setosa setosa      1
6          5.0         3.4          1.5         0.2  setosa setosa      1
  versicolor virginica
1          0         0
2          0         0
3          0         0
4          0         0
5          0         0
6          0         0

# print(dim(modelerDataModel))
[1] 6 9

# print(modelerDataModel)
                       X1          X2           X3          X4      X5     X6
fieldName    Sepal.Length Sepal.Width Petal.Length Petal.Width Species   pred
fieldLabel                                                                   
fieldStorage         real        real         real        real  string string
fieldMeasure                                                                 
fieldFormat                                                                  
fieldRole                                                                    
                 X7         X8        X9
fieldName    setosa versicolor virginica
fieldLabel                              
fieldStorage   real       real      real
fieldMeasure                            
fieldFormat                             
fieldRole  

[表节点的输出（为什么 11cols 是？？？）]

Answer 1

我找到了一种方法来解决我的简单示例......很难理解。从 R 语言的角度来看，这是一个错误。（但是这个方法在其他情况下不起作用，有谁知道如何避免这个错误？）

questions_modelerData <- cbind(modelerData, pred_forest, prob_forest)

modelerData <- cbind(modelerData, pred_forest, 
                     setosa = prob_forest[,1], 
                     versicolor = prob_forest[,2],   
                     virginica = prob_forest[,3])

identical(questions_modelerData, modelerData)
# [1] TRUE
# but this modelerData works unlike the question's.

该死的。