G=c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2)
x1=c(-1.9,-6.9,5.2,5.0,7.3,6.8,0.9,-12.5,1.5,3.8,0.2,-0.1,0.4,2.7,2.1,-4.6,-1.7,-2.6,2.6,2.8)
x2=c(3.2,0.4,2.0,2.5,0.0,12.7,-5.4,-2.5,1.3,6.8,6.2,7.5,14.6,8.3,0.8,4.3,10.9,13.1,12.8,10.0)
a=data.frame(G,x1,x2)
library(MASS)
ld=lda(G~x1+x2)
z=predict(ld)
求出的[size=14.6667px]线性判别方程:y = -0.1035305 * x1 + 0.2247957 * x2
newG=z$class
Y=cbind(G,z$x,newG)
G LD1 newG
1 1 -0.28890415 1 (x1=-1.9,x2=3.2,请问该行是如何验证的?-0.28890415是咋样得出的?)
2 1 -0.45813751 1
3 1 -1.22926991 1
4 1 -1.09643832 1
5 1 -1.88265685 1
6 1 1.06123690 2
7 1 -2.51351622 1
8 1 -0.59384584 1
9 1 -1.04154104 1
10 1 -0.00291083 1
11 2 0.19823938 2
12 2 0.52294512 2
13 2 2.09555201 2
14 2 0.44253032 2
15 2 -1.21192973 1
16 2 0.21552295 2
17 2 1.44873422 2
18 2 2.03507109 2
19 2 1.47839701 2
20 2 0.82092141 2