Linear Discriminant Analysis

问题

In this example (from here), the remote-sensing data are used. In this data set, the observations are grouped into five crops: clover, corn, cotton, soybeans, and sugar beets. Four measures called x1 through x4 make up the descriptive variables.

dat <- read.table(header=T, text='
Crop       x1 x2 x3 x4
Corn       16 27 31 33
Corn       15 23 30 30
Corn       16 27 27 26
Corn       18 20 25 23
Corn       15 15 31 32
Corn       15 32 32 15
Corn       12 15 16 73
Soybeans   20 23 23 25
Soybeans   24 24 25 32
Soybeans   21 25 23 24
Soybeans   27 45 24 12
Soybeans   12 13 15 42
Soybeans   22 32 31 43
Cotton     31 32 33 34
Cotton     29 24 26 28
Cotton     34 32 28 45
Cotton     26 25 23 24
Cotton     53 48 75 26
Cotton     34 35 25 78
Sugarbeets 22 23 25 42
Sugarbeets 25 25 24 26
Sugarbeets 34 25 16 52
Sugarbeets 54 23 21 54
Sugarbeets 25 43 32 15
Sugarbeets 26 54  2 54
Clover     12 45 32 54
Clover     24 58 25 34
Clover     87 54 61 21
Clover     51 31 31 16
Clover     96 48 54 62
Clover     31 31 11 11
Clover     56 13 13 71
Clover     32 13 27 32
Clover     36 26 54 32
Clover     53 08 06 54
Clover     32 32 62 16
')

Adjusting a discriminant function with all the X variables:

library(MASS)
cropLda <- lda(dat[,-1],dat[,1])

With this plot

cropProjection <- cbind(scale(as.matrix(dat[,-1]), scale=FALSE) %*% cropLda$scaling,dat[,1,drop=FALSE])

cropProjection$row_num = 1:nrow(cropProjection)
p <- ggplot(data=cropProjection, aes(x=LD1,y=LD2, col=Crop)) + 
  geom_point() + geom_text(aes(label = row_num))
print(p)

How can I extract the Linear Discriminant Function for Crop (sas output table)

来源：https://stackoverflow.com/questions/30495710/linear-discriminant-analysis

标签

multivariate-testing