#title 조건트리

{{{
library(party)
x <-  sqlQuery(conn, "select top 1000 new_type 신규유형, hh 접속시간대, case when time >= 5 then '5이상' else '5미만' end time
 from ods.dbo.v_h2 where join_dt = '20120411'")
tree <- ctree(time ~ 신규유형 +  접속시간대, data=x)
#tree <- ctree(time ~ 신규유형 +  접속시간대, controls = ctree_control(maxdepth = 5), data=x) 
plot(tree)
}}}

attachment:조건트리/ctree.png


{{{
> tree <- randomForest(time ~ 신규유형 +  접속시간대, data=x)
> print(tree) # view results 

Call:
 randomForest(formula = time ~ 신규유형 + 접속시간대, data = x) 
               Type of random forest: classification
                     Number of trees: 500
No. of variables tried at each split: 1

        OOB estimate of  error rate: 23.39%
Confusion matrix:
       10미만 10이상 class.error
10미만   1736      0           0
10이상    530      0           1
> importance(tree) # importance of each predictor
           MeanDecreaseGini
신규유형           18.15337
접속시간대          9.90380
> 
}}}


{{{
library(party)
tree <- ctree(Volume ~ ., data=trees)
plot(tree, terminal_panel = node_density)
#plot(tree, terminal_panel = node_barplot(tree))
}}}
attachment:조건트리/ctree02.png

http://rgm3.lab.nig.ac.jp/RGM/R_rdfile?f=party/man/panelfunctions.Rd&d=R_CC


{{{
library(partykit) 
    airct <- ctree(Ozone ~ ., data = airq)
    class(airct)  # different class from before
    # "constparty" "party"  
plot(airct, gp = gpar(fontsize = 6),     # font size changed to 6
  inner_panel=node_inner,
  ip_args=list(
       abbreviate = TRUE, 
       id = FALSE)
  )

library(partykit) 
tree <- ctree(revisit_cnt ~ ., controls = ctree_control(maxdepth = 5), data = training)
plot(tree, gp = gpar(fontsize = 8))
}}}


{{{
png("mytree.png",res=80,height=800,width=1600) 
plot(mytree) 
dev.off() 
}}}

terminal_node 커스터마이징하기
http://stackoverflow.com/questions/13959431/how-to-get-all-terminal-nodes-weight-response-prediction-ctree-in-r


{{{
library(party)
library(caret)
gtree <- ctree(Species ~ ., data = iris)
plot(gtree, inner_panel = node_barplot,
     edge_panel = function(...) invisible(), tnex = 1)
}}}
attachment:조건트리/ctree_2.png

tree의 크기 조정하기
http://stackoverflow.com/questions/13751962/how-to-plot-a-large-ctree-to-avoid-overlapping-nodes

==== bar plot 수평으로 세우기 ====
--http://stackoverflow.com/questions/11961923/rotate-classification-tree-terminal-barplot-axis-r
{{{
# Note inclusion of horiz = FALSE
alt_node_barplot <- function (ctreeobj, col = "black", fill = NULL, beside = NULL, 
    ymax = NULL, ylines = NULL, widths = 1, gap = NULL, reverse = NULL, 
    id = TRUE, horiz = FALSE)
{
    getMaxPred <- function(x) {
        mp <- max(x$prediction)
        mpl <- ifelse(x$terminal, 0, getMaxPred(x$left))
        mpr <- ifelse(x$terminal, 0, getMaxPred(x$right))
        return(max(c(mp, mpl, mpr)))
    }
    y <- response(ctreeobj)[[1]]
    if (is.factor(y) || class(y) == "was_ordered") {
        ylevels <- levels(y)
        if (is.null(beside)) 
            beside <- if (length(ylevels) < 3) 
                FALSE
            else TRUE
        if (is.null(ymax)) 
            ymax <- if (beside) 
                1.1
            else 1
        if (is.null(gap)) 
            gap <- if (beside) 
                0.1
            else 0
    }
    else {
        if (is.null(beside)) 
            beside <- FALSE
        if (is.null(ymax)) 
            ymax <- getMaxPred(ctreeobj@tree) * 1.1
        ylevels <- seq(along = ctreeobj@tree$prediction)
        if (length(ylevels) < 2) 
            ylevels <- ""
        if (is.null(gap)) 
            gap <- 1
    }
    if (is.null(reverse)) 
        reverse <- !beside
    if (is.null(fill)) 
        fill <- gray.colors(length(ylevels))
    if (is.null(ylines)) 
        ylines <- if (beside) 
            c(3, 2)
        else c(1.5, 2.5)
    # My edit do not work if beside is not true
    #################################################
    if(!beside) horiz = FALSE
    #################################################

    rval <- function(node) {
        pred <- node$prediction
        if (reverse) {
            pred <- rev(pred)
            ylevels <- rev(ylevels)
        }
        np <- length(pred)
        nc <- if (beside) 
            np
        else 1
        fill <- rep(fill, length.out = np)
        widths <- rep(widths, length.out = nc)
        col <- rep(col, length.out = nc)
        ylines <- rep(ylines, length.out = 2)
        gap <- gap * sum(widths)
        #######################################################
        if (!horiz){
            yscale <- c(0, ymax)
            xscale <- c(0, sum(widths) + (nc + 1) * gap)
        } else {
            xscale <- c(0, ymax)
            yscale <- c(0, sum(widths) + (nc + 1) * gap)
        }                    
        #######################################################
        top_vp <- viewport(layout = grid.layout(nrow = 2, ncol = 3, 
            widths = unit(c(ylines[1], 1, ylines[2]), c("lines", 
                "null", "lines")), heights = unit(c(1, 1), c("lines", 
                "null"))), width = unit(1, "npc"), height = unit(1, 
            "npc") - unit(2, "lines"), name = paste("node_barplot", 
            node$nodeID, sep = ""))
        pushViewport(top_vp)
        grid.rect(gp = gpar(fill = "white", col = 0))
        top <- viewport(layout.pos.col = 2, layout.pos.row = 1)
        pushViewport(top)
        mainlab <- paste(ifelse(id, paste("Node", node$nodeID, 
            "(n = "), "n = "), sum(node$weights), ifelse(id, 
            ")", ""), sep = "")
        grid.text(mainlab)
        popViewport()
        plot <- viewport(layout.pos.col = 2, layout.pos.row = 2, 
            xscale = xscale, yscale = yscale, name = paste("node_barplot", 
                node$nodeID, "plot", sep = ""))
        pushViewport(plot)
        if (beside) {
            #############################################################
            if(!horiz){
                xcenter <- cumsum(widths + gap) - widths/2
                for (i in 1:np) {
                    grid.rect(x = xcenter[i], y = 0, height = pred[i], 
                      width = widths[i], just = c("center", "bottom"), 
                      default.units = "native", gp = gpar(col = col[i], 
                        fill = fill[i]))
                }
                if (length(xcenter) > 1) 
                    grid.xaxis(at = xcenter, label = FALSE)
                grid.text(ylevels, x = xcenter, y = unit(-1, "lines"), 
                    just = c("center", "top"), default.units = "native", 
                    check.overlap = TRUE)
                grid.yaxis()
            } else {
                ycenter <- cumsum(widths + gap) - widths/2
                for (i in 1:np) {
                    grid.rect(y = ycenter[i], x = 0, width = pred[i], 
                    height = widths[i], just = c("left", "center"), 
                    default.units = "native", gp = gpar(col = col[i], 
                     fill = fill[i]))
                }
                if (length(ycenter) > 1) 
                    grid.yaxis(at = ycenter, label = FALSE)
                        grid.text(ylevels, y = ycenter, x = unit(-1, "lines"), 
                        just = c("right", "center"), default.units = "native", 
                         check.overlap = TRUE)
                grid.xaxis()
            }
        #############################################################
        }
        else {
            ycenter <- cumsum(pred) - pred
            for (i in 1:np) {
                grid.rect(x = xscale[2]/2, y = ycenter[i], height = min(pred[i], 
                  ymax - ycenter[i]), width = widths[1], just = c("center", 
                  "bottom"), default.units = "native", gp = gpar(col = col[i], 
                  fill = fill[i]))
            }
            if (np > 1) {
                grid.text(ylevels[1], x = unit(-1, "lines"), 
                  y = 0, just = c("left", "center"), rot = 90, 
                  default.units = "native", check.overlap = TRUE)
                grid.text(ylevels[np], x = unit(-1, "lines"), 
                  y = ymax, just = c("right", "center"), rot = 90, 
                  default.units = "native", check.overlap = TRUE)
            }
            if (np > 2) {
                grid.text(ylevels[-c(1, np)], x = unit(-1, "lines"), 
                  y = ycenter[-c(1, np)], just = "center", rot = 90, 
                  default.units = "native", check.overlap = TRUE)
            }
            grid.yaxis(main = FALSE)
        }
        grid.rect(gp = gpar(fill = "transparent"))
        upViewport(2)
    }
    return(rval)
}
}}}

{{{
plot(ctree, terminal_panel = alt_node_barplot(ctree, horiz = TRUE))
}}}


https://luisdva.github.io/rstats/Plotting-conditional-inference-trees-in-R/