list_node: list_node

In jwolfson/visparty: Visualize conditional regression trees

Usage

list_node(newtree, node_id = 1, start_criteria = character(0))

Arguments

newtree
node_id
start_criteria

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (newtree, node_id = 1, start_criteria = character(0)) 
{
    if (nodes(newtree, node_id)[[1]]$terminal) {
        prediction <- ptree_y(newtree, node_id)
        ypred <- paste(start_criteria, ",y =", prediction, ";")
        return(ypred)
    }
    left_node_id <- ptree_left(newtree, node_id)
    right_node_id <- ptree_right(newtree, node_id)
    if (is.null(left_node_id) != is.null(right_node_id)) {
        print("left node ID != right node id")
    }
    ypred <- character(0)
    if (!is.null(left_node_id)) {
        new_criteria <- paste(start_criteria, ptree_criteria(newtree, 
            node_id, T), sep = ",")
        if (1 == node_id) 
            new_criteria <- ptree_criteria(newtree, node_id, 
                T)
        ypred <- list_node(newtree, left_node_id, new_criteria)
    }
    if (!is.null(right_node_id)) {
        new_criteria <- paste(start_criteria, ptree_criteria(newtree, 
            node_id, F), sep = ",")
        if (1 == node_id) 
            new_criteria <- ptree_criteria(newtree, node_id, 
                F)
        ypred <- paste(ypred, list_node(newtree, right_node_id, 
            new_criteria))
    }
    return(ypred)
  }

jwolfson/visparty documentation built on May 20, 2019, 6:27 a.m.