My code

load P$.$mat

$[$coeff$,$score,latent,taquared,explained,mu$]=$ pca$($P$)$;

plot$($cumsum$($explained$))$

$\%$load T$.$mat

$\%[$coeff$,$score,latent,taquared,explained,mu$]=$ pca$($T$)$;

$\%$plot$($cumsum$($explained$))$

$\%$m$1=$ P$([12345678910],$:$)$

$\%$m$1=$ P$($:$,1$:$284)$

$\%$m$1=$ P$(1$:$10,1$:$10)$

$\%$m$1=$ P$(1$:$10,$:$)$

m$1=$ P$($:$,1$:$10)$

$\%$m$2=$ T$($:$,1$:$10)$

$\%$ Split the data

Ptrn$=$m$1($:$,1$:$6)\text{'}$; $\%1$st $2/3,$ input

Ttrn$=$T$(1$:$6)\text{'}$; $\%1$st $2/3,$ desired output

Pval$=$m$1($:$,7$:end$)\text{'}$; $\%2$nd $1/3,$ input

Tval$=$T$(7$:end$)\text{'}$; $\%2$nd $1/3,$ desired output

MdlLinear $=$ fitcdiscr$($Ptrn$,$Ttrn$)$;

$[$YtrnLBL$,$ YtrnSCR$,$ ~$]=$ predict$($MdlLinear$,$Ptrn$)$;

$[$YvalLBL$,$ YvalSCR, ~$]=$ predict$($MdlLinear$,$Pval$)$;

$[$X$1,$Y$1,$Tr$1,$AUC$1]=$ perfcurve$($Ttrn$,$YtrnSCR$($:$,2),1)$;

$\%$ Training

scoresPOS$=$YtrnSCR$($Ttrn$==1,2)$;

scoresNEG$=$YtrnSCR$($Ttrn$==-1,2)$;

d$\_$primeTRN$=$abs$($mean$($scoresPOS$)-$mean$($scoresNEG$))/$sqrt$(0\mathrm{.}5*$var$($scoresPOS$)+0\mathrm{.}5*$var$($scoresNEG$))\%$ d$\text{'}$

figure, plot$($X$1,$Y$1),$xlabel$(\text{'}$FAR or FPR$\text{'}),$ylabel$(\text{'}$GAR or TPR$\text{'}),$title$([\text{'}$Fold $1$ Training ROC, AUC$=\text{'}$ num$2$str$($AUC$1)])$

ind$1=$find$((1-$Y$1)$