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Version 1.7.0  (2003-04-16)

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> library(MASS);
> test <- read.table("madham1.txt", sep="");
> train <- read.table("disputed1.txt", sep="");
> cl <- factor(c(rep("m",14), rep("h",18)))
> 
> test;
       V1      V2      V3
1  27.036 206.943  95.794
2  18.250 212.915 113.243
3  21.033 202.583  88.930
4  29.261 211.161  88.386
5  20.353 236.943  76.805
6  18.254 216.064  91.271
7  26.494 204.622 104.284
8  18.732 211.095  97.983
9  30.877 218.177  91.756
10 18.276 203.793 121.724
11 10.875 201.891  90.780
12 17.625 200.383 101.533
13 14.991 209.506  85.558
14 23.694 210.016  97.469
15 24.621 224.116 100.379
16 26.266 189.962  96.623
17 20.870 215.364 116.341
18 23.162 212.991  98.187
19 26.849 219.352 100.304
20 28.869 212.911 109.864
21 22.388 215.019 106.343
22 27.518 238.305  97.964
23 23.129 241.800  93.776
24 20.034 232.937 100.170
25 27.383 232.227 114.797
26 22.344 231.380 110.725
27 24.324 232.432  85.135
28 24.309 216.651  94.196
29 27.043 230.453  85.832
30 28.024 226.647  92.429
31 30.151 235.176 109.548
32 36.999 231.627  96.300
> train;
       V1      V2      V3
1  21.290 226.277 107.664
2  17.257 205.268  96.276
3  25.118 225.536  88.435
4  21.727 217.273 114.612
5  23.611 208.796  82.407
6  19.549 232.581  96.241
7  29.007 210.914 117.011
8  29.448 192.638 101.840
9  18.611 226.509 107.127
10 28.325 207.393  98.896
11 34.439 220.076  91.138
12 22.757 213.391  92.348
> cl;
 [1] m m m m m m m m m m m m m m h h h h h h h h h h h h h h h h h h
Levels: h m
> 
> z <- lda(test, cl);
> 
> predict(z, train);
$class
 [1] h m h h m h h m h m h m
Levels: h m

$posterior
            h         m
1  0.84895002 0.1510500
2  0.07642057 0.9235794
3  0.66458531 0.3354147
4  0.78798756 0.2120124
5  0.10783580 0.8921642
6  0.76868996 0.2313100
7  0.88626149 0.1137385
8  0.20439877 0.7956012
9  0.77378023 0.2262198
10 0.49121862 0.5087814
11 0.87246060 0.1275394
12 0.29604457 0.7039554

$x
    
            LD1
  1  -0.7615787
  2   1.7201800
  3  -0.1482016
  4  -0.5182784
  5   1.4972283
  6  -0.4524405
  7  -0.9537943
  8   1.0536273
  9  -0.4694147
  10  0.2747550
  11 -0.8771848
  12  0.7636922

>