LDA贡献双程图

Question

我试图为线性判别分析(LDA)创建一个双图。我正在使用从这里获得的代码的修改版本https://stats.stackexchange.com/questions/82497/can-the-scaling-values-in-a-linear-discriminant-analysis-lda-be-used-to-plot-e。

然而，我有80个变量，使得双情节极难读懂。由于它们的箭头长度很长，其余的标签在中间被缩小，高贡献变量使这种情况更加恶化。因此，我试图实现的是一个双图，所有可变箭头都是相同长度的，它们的相对贡献(标度)用分级颜色来区分。到目前为止，我已经得到了分级的颜色，但我无法找到使箭头长度相同的方法。据我所知，geom_text和geom_segment使用LD1和LD2值来确定箭头的长度和方向。我怎样才能覆盖长度？

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代码：

library(ggplot2)
library(grid)
library(MASS)
data(iris)


iris.lda <- lda(as.factor(Species)~.,
                data=iris)

#Project data on linear discriminants
iris.lda.values <- predict(iris.lda, iris[,-5])

#Extract scaling for each predictor and
data.lda <- data.frame(varnames=rownames(coef(iris.lda)), coef(iris.lda))

#coef(iris.lda) is equivalent to iris.lda$scaling

data.lda$length <- with(data.lda, sqrt(LD1^2+LD2^2))

#Plot the results
p <- qplot(data=data.frame(iris.lda.values$x),
           main="LDA",
           x=LD1,
           y=LD2,
           colour=iris$Species)+stat_ellipse(geom="polygon", alpha=.3, aes(fill=iris$Species))
p <- p + geom_hline(aes(yintercept=0), size=.2) + geom_vline(aes(xintercept=0), size=.2)
p <- p + theme(legend.position="right")
p <- p + geom_text(data=data.lda,
                   aes(x=LD1, y=LD2,
                       label=varnames, 
                       shape=NULL, linetype=NULL,
                       alpha=length, position="identity"),
                   size = 4, vjust=.5,
                   hjust=0, color="red")
p <- p + geom_segment(data=data.lda,
                      aes(x=0, y=0,
                          xend=LD1, yend=LD2,
                          shape=NULL, linetype=NULL,
                          alpha=length),
                      arrow=arrow(length=unit(0.1,"mm")),
                      color="red")
p <- p + coord_flip()

print(p)

Answer 1

像这样的怎么样？我们得做一些三角学才能使长度相等。请注意，等式位于绘图坐标中，因此，如果您希望实际以相同的大小出现，则需要添加coord_equal。

(我清理了你的绘图代码，因为很多代码都很乱。)

rad <- 3 # This sets the length of your lines.
data.lda$length <- with(data.lda, sqrt(LD1^2+LD2^2))
data.lda$angle <- atan2(data.lda$LD1, data.lda$LD2)
data.lda$x_start <- data.lda$y_start <- 0
data.lda$x_end <- cos(data.lda$angle) * rad
data.lda$y_end <- sin(data.lda$angle) * rad

#Plot the results
ggplot(cbind(iris, iris.lda.values$x),
       aes(y = LD1, x = LD2, colour = Species)) + 
  stat_ellipse(aes(fill = Species), geom = "polygon", alpha = .3) +
  geom_point() +
  geom_hline(yintercept = 0, size = .2) + 
  geom_vline(xintercept = 0, size = .2) +
  geom_text(aes(y = y_end, x = x_end, label = varnames, alpha = length),
            data.lda, size = 4, vjust = .5, hjust = 0, colour = "red") +
  geom_spoke(aes(x_start, y_start, angle = angle, alpha = length), data.lda, 
             color = "red", radius = rad, size = 1) +
  ggtitle("LDA") +
  theme(legend.position = "right")

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Answer 2

我想我有一个更简单的代码来实现双情节。我希望下面的代码能有所帮助。我使用了IRIS数据集进行分析。

library(readr)
IR <- read_csv("D:/Keerthesh/R Folder/DataSet/Iris.csv")

# --- data partition -- #
set.seed(555)
IRSam <- sample.int(n = nrow(IR), size = floor(.60*nrow(IR)), replace = FALSE, prob = NULL)
IRTrain <- IR[IRSam,]
IRTest <- IR[-IRSam,]

library(MASS)
IR.lda <- lda(Species~. -Id, data=IRTrain)
print(IR.lda)

要绘制双图，您需要从github安装ggord包。

library(devtools)
install_github('fawda123/ggord') --- Used to install ggord from github we need to run devtools to achieve this.
library(ggord)
ggord(IR.lda, IRTrain$Species, ylim=c(-5,5), xlim=c(-10,10))

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