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Version 1.5.1  (2002-06-17)

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> invisible(options(echo = TRUE))
> library(MASS)
> 
> ntw.lrn <- read.table("../lrn/ntw_lrn.dat",header=T,sep=",")
> 
> ntw.names <- names(ntw.lrn)
> 
> y <- ntw.lrn$connection.type
> 
> f23 <- ntw.lrn$count
> f29 <- ntw.lrn$same.srv.rate
> f <- cbind(f23,f29)
> 
> m.neptune <- cbind(mean(f23[y=="neptune"]),mean(f29[y=="neptune"]))
> m.normal <- cbind(mean(f23[y=="normal"]),mean(f29[y=="normal"]))
> m.smurf <- cbind(mean(f23[y=="smurf"]),mean(f29[y=="smurf"]))
> 
> real <- c(0.1,0.8,0.1)
> 
> fit <- lda(cbind(f23,f29),y,prior=real) 
> print(fit$prior) 
neptune  normal   smurf 
    0.1     0.8     0.1 
> 
> size <- 100
> 
> f23.axis <- seq(from=min(f23),to=max(f23),length=100)
> f29.axis <- seq(from=min(f29),to=max(f29),length=100)
> 
> grid <- mat.or.vec(size*size,2)
> for (i in 1:size) {
+   for (j in 1:size) {
+     grid[size*(j-1)+i,1] <- f23.axis[i];
+     grid[size*(j-1)+i,2] <- f29.axis[j];  
+   }
+ }
> 
> pred <- predict(fit,grid,prior=real)
> 
> yhat <- pred$class
> 
> edge <- mat.or.vec(size*size,1)
> edge <- as.logical(edge)
> for (i in 1:size) { 
+   for (j in 1:size) {
+     cntr <- size*(j-1)+i
+     left <- cntr - size
+     down <- cntr - 1
+     if ( (left > 0) && (down > 0) ) {
+       edge[cntr] <- (yhat[left] != yhat[cntr]) || (yhat[down] != yhat[cntr])
+     }
+     if (i == 1) edge[cntr] <- FALSE
+   }
+ }
> 
> source("psopts.r")
> postscript(file="ntw_lda_real.eps")
> par.default <- par(no.readonly=TRUE) 
> plot(grid,type='n',xlab=ntw.names[23],ylab=ntw.names[29])
>   points(grid[yhat=="neptune",],pch='.',col="red")
>   points(grid[yhat=="normal",],pch='.',col="green")
>   points(grid[yhat=="smurf",],pch='.',col="blue")
>   points(m.neptune,pch="o",col="red")
>   points(m.normal,pch="o",col="green")
>   points(m.smurf,pch="o",col="blue")
>   points(grid[edge,],pch='+',col="black",cex=0.4)
> dev.off()
null device 
          1 
> 
> proc.time()
[1] 57.66  0.89 58.66  0.00  0.00
>