将ctree输出转换为JSON格式(用于D3树布局)

问题描述:

我正在开发一个需要运行ctree然后以交互模式绘制它的项目 - 就像'D3.js'树布局一样,我的主要障碍是将ctree输出转换为json格式,稍后由javascript使用。将ctree输出转换为JSON格式(用于D3树布局)

以下是我所需要的(与例如从虹膜数据):

> 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 

现在我想的ctee输出转换成使用某种算法如下JSON格式(我手工做的),不过,这可能不是将其转换的最佳方式:

{"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} 
    ]}] } 
     ]} 

这里有两个R的两张照片和D3.js图:

enter image description hereenter image description here

我已经尝试在ctree对象上使用RJSONIO,这并没有多大帮助。

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,没有人有任何想法的算法,可以将一个输出转换为另一个?

在此先感谢您的帮助!

诀窍是提取irisct对象的有用位,并且只将它们转换为JSON。事情是这样的:

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) 

我想这个答案了通过明智使用unclass功能。例如:

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

包中的打印方法,party:::print.SplittingNodeparty:::print.TerminalNode也非常有用的。 (输入party:::print.并自动完成以查看可用内容。)