Wie wissenschaftliche Notation für Rplot-Diagramm zu entfernen

Question

Ich entwickelte dieses R-Skript, um einen Entscheidungsfluss Rplot-Diagramm zu fahren, aber ich kann es nicht zum Anzeigen von numerischen Werten anstelle von wissenschaftlicher Notation. Ich habe gestern die Hälfte des Arbeitstages damit verbracht, es numerisch zu machen, indem ich die Beispiele befolge, die ich auf stackoverflow gefunden habe, aber bisher kein Glück. Siehe Code und Screenshot für Details.

#automatically convert columns with few unique values to factors 
convertCol2factors<-function(data, minCount = 3) 
{ 
    for (c in 1:ncol(data)) 
    if(is.logical(data[, c])){ 
     data[, c] = as.factor(data[, c]) 
    }else{ 
     uc<-unique(data[, c]) 
     if(length(uc) <= minCount) 
     data[, c] = as.factor(data[, c]) 
    } 
    return(data) 
} 

#compute root node error 
rootNodeError<-function(labels) 
{ 
    ul<-unique(labels) 
    g<-NULL 
    for (u in ul) g = c(g, sum(labels == u)) 
    return(1-max(g)/length(labels)) 
} 
# this function is almost identical to fancyRpartPlot{rattle} 
# it is duplicated here because the call for library(rattle) may trigger GTK load, 
# which may be missing on user's machine 
replaceFancyRpartPlot<-function (model, main = "", sub = "", palettes, ...) 
{ 

    num.classes <- length(attr(model, "ylevels")) 

    default.palettes <- c("Greens", "Blues", "Oranges", "Purples", 
         "Reds", "Greys") 
    if (missing(palettes)) 
    palettes <- default.palettes 

    missed <- setdiff(1:6, seq(length(palettes))) 
    palettes <- c(palettes, default.palettes[missed]) 
    numpals <- 6 
    palsize <- 5 
    pals <- c(RColorBrewer::brewer.pal(9, palettes[1])[1:5], 
      RColorBrewer::brewer.pal(9, palettes[2])[1:5], RColorBrewer::brewer.pal(9, 
                        palettes[3])[1:5], RColorBrewer::brewer.pal(9, palettes[4])[1:5], 
      RColorBrewer::brewer.pal(9, palettes[5])[1:5], RColorBrewer::brewer.pal(9, 
                        palettes[6])[1:5]) 
    if (model$method == "class") { 
    yval2per <- -(1:num.classes) - 1 
    per <- apply(model$frame$yval2[, yval2per], 1, function(x) x[1 + 
                    x[1]]) 
    } 
    else { 
    per <- model$frame$yval/max(model$frame$yval) 
    } 
    per <- as.numeric(per) 
    if (model$method == "class") 
    col.index <- ((palsize * (model$frame$yval - 1) + trunc(pmin(1 + 
                    (per * palsize), palsize)))%%(numpals * palsize)) 
    else col.index <- round(per * (palsize - 1)) + 1 
    col.index <- abs(col.index) 
    if (model$method == "class") 
    extra <- 104 
    else extra <- 101 
    rpart.plot::prp(model, type = 2, extra = extra, box.col = pals[col.index], 
        nn = TRUE, varlen = 0, faclen = 0, shadow.col = "grey", 
        fallen.leaves = TRUE, branch.lty = 3, ...) 
    title(main = main, sub = sub) 
} 

###############Upfront input correctness validations (where possible)################# 

pbiWarning<-"" 
pbiInfo<-"" 

dataset <- dataset[complete.cases(dataset[, 1]), ] #remove rows with corrupted labels 
dataset = convertCol2factors(dataset) 
nr <- nrow(dataset) 
nc <- ncol(dataset) 
nl <- length(unique(dataset[, 1])) 

goodDim <- (nr >=minRows && nc >= 2 && nl >= 2) 


##############Main Visualization script########### 
set.seed(randSeed) 
opt = NULL 
dtree = NULL 

if(autoXval) 
    xval<-autoXvalFunc(nr) 

dNames <- names(dataset) 
X <- as.vector(dNames[-1]) 

form <- as.formula(paste('`', dNames[1], '`', "~ .", sep = "")) 

# Run the model 
if(goodDim) 
{ 
    for(a in 1:maxNumAttempts) 
    { 
    dtree <- rpart(form, dataset, control = rpart.control(minbucket = minBucket, cp = complexity, maxdepth = maxDepth, xval = xval)) #large tree 
    rooNodeErr <- rootNodeError(dataset[, 1]) 
    opt <- optimalCPbyXError(as.data.frame(dtree$cptable)) 

    dtree<-prune(dtree, cp = opt$CP) 
    if(opt$ind > 1) 
     break; 
    } 
} 

#info for classifier 
if(showInfo && !is.null(dtree) && dtree$method == 'class') 
    pbiInfo <- paste("Rel error = ", d2form(opt$relErr * rooNodeErr), 
       "; CVal error = ", d2form(opt$xerror * rooNodeErr), 
       "; Root error = ", d2form(rooNodeErr), 
       ";cp = ", d2form(opt$CP, 3), sep = "") 

if(goodDim && opt$ind>1) 
{ 
    #fancyRpartPlot(dtree, sub = pbiInfo) 
    replaceFancyRpartPlot(dtree, sub = pbiInfo) 


}else{ 
    if(showWarnings) 
    pbiWarning <- ifelse(goodDim, paste("The tree depth is zero. Root error = ", d2form(rooNodeErr), sep = ""), 
            "Wrong data dimensionality") 

    plot.new() 
    title(main = NULL, sub = pbiWarning, outer = FALSE, col.sub = "gray40") 
} 
remove("dataset") 

Auch, wie kann ich sagen, was "n" bedeutet von dem Foto unten? (Ich habe diesen Code von einem Projekt kopiert).

Answer 1

Versuchen Sie, digits = -2 zu dem prp Aufruf in Ihrem Code

hinzuzufügen