Question

我正在开发一个项目，需要运行ctree，然后以交互模式绘制它 - 就像'D3.js'树布局一样，我的主要障碍是转换ctree输出为json格式，稍后由javascript使用。

以下是我需要的（例如来自虹膜数据）：

> library(party)
> irisct <- ctree(Species ~ .,data = iris)
> irisct

     Conditional inference tree with 4 terminal nodes

Response:  Species 
Inputs:  Sepal.Length, Sepal.Width, Petal.Length, Petal.Width 
Number of observations:  150 

1) Petal.Length <= 1.9; criterion = 1, statistic = 140.264
  2)*  weights = 50 
1) Petal.Length > 1.9
  3) Petal.Width <= 1.7; criterion = 1, statistic = 67.894
    4) Petal.Length <= 4.8; criterion = 0.999, statistic = 13.865
      5)*  weights = 46 
    4) Petal.Length > 4.8
      6)*  weights = 8 
  3) Petal.Width > 1.7
    7)*  weights = 46

现在我想使用某种算法将ctee输出转换为以下JSON格式（我手动完成），但这可能不是转换它的最佳方式：

{"name" : "Petal.Length <= 1.9  criterion = 1","value": 60, "children" : [
            {"name" : "n=50" ,"value": 60},
            {"name" : "Petal.Length > 1.9 criterion = 1","value": 60, "children": [
                  {"name" : "n=46","value": 60 },
                  {"name" : "Petal.Length > 4.8","value": 60, "children" :[
            {"name" : "Petal.Width > 1.7" ,"value": 60},
            {"name" : "46" ,"value": 60}
    ]}] }
      ]}

以下是R和D3.js图的两张图片：

enter image description here

我已经尝试在ctree对象上使用RJSONIO，这没什么用。

有没有人将ctree对象/输出转换为JSON以使用D3.js树布局？如果没有，是否有人知道可以将一个输出转换为另一个输出的算法？

提前感谢您的帮助！

Answer 1

诀窍是提取irisct对象的有用位，并仅将它们转换为JSON。像这样：

get_ctree_parts <- function(x, ...)
{
  UseMethod("get_ctree_parts")
}

get_ctree_parts.BinaryTree <- function(x, ...)
{
  get_ctree_parts(attr(x, "tree"))
}

get_ctree_parts.SplittingNode <- function(x, ...)
{
  with(
    x,
    list(
      nodeID       = nodeID,
      variableName = psplit$variableName,
      splitPoint   = psplit$splitpoint,
      pValue       = 1 - round(criterion$maxcriterion, 3),
      statistic    = round(max(criterion$statistic), 3),
      left         = get_ctree_parts(x$left),
      right        = get_ctree_parts(x$right)
    )
  )
}

get_ctree_parts.TerminalNode <- function(x, ...)
{
  with(
    x,
    list(
      nodeID     = nodeID,
      weights    = sum(weights),
      prediction = prediction
    )
  )
}

useful_bits_of_irisct <- get_ctree_parts(irisct)
toJSON(useful_bits_of_irisct)

我通过明智地使用unclass函数来找出这个答案。例如：

unclass(irisct)
unclass(attr(irisct, "tree"))
unclass(attr(irisct, "tree")$psplit)

包中的打印方法party:::print.SplittingNode和party:::print.TerminalNode也非常有用。（键入party:::print.并自动填充以查看可用内容。）

将ctree输出转换为JSON格式（用于D3树布局）

1 个答案: