Stat841f09 - Wiki Course Notes

# Comwindexphptitle stat841pr intable yes 1274 10092013

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Unformatted text preview: Stat841 - Wiki Cour se Notes Those familiar with the programming language C will find the s r n fline refreshingly familiar; those with no exposure to C are directed to Matlab's s r n f pit pit (http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/ref/sprintf.html) page. Essentially, this code sets up the equation of the line in the form 0 = a + b + c . We then use the e p o x y zlt (http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/ref/ezplot.html) function to plot the line. The 2-3 data after LDA is performed. The line shows where the two classes are split. Let's perform the same steps, except this time using QDA. The main difference with QDA is a slightly different call to c a s f , and a more complicated procedure lsiy to plot the line. > [ls,err PSEIR lg,cef =casf(ape sml,gop 'udai'; > cas ro, OTRO, op of] lsiysml, ape ru, qartc) > sm(ls=gop >u cas=ru) as= n 31 7 > k=cef12.os; > of(,)cnt > l=cef12.ier > of(,)lna; > q=cef12.udai; > of(,)qartc > f=srnf' =%+gx%*+gx2%*.y%*.2,k l q11,q12+(,) q22) > pit(0 g%*+gy%*^+gx*+gy^' , , (,) (,)q21, (,); > epo(,[i(ape:1) mxsml(,),mnsml(,),mxsml(,)]; > zltf mnsml(,), a(ape:1) i(ape:2) a(ape:2)) The 2-3 data after QDA is performed. The curved line shows where QDA splits the two classes. Note that it is only correct 2 in 2 more data points compared to LDA; we can see a blue point and a red point that lie on the correct side of the curve that do not lie on the correct side of the line. wikicour senote.com/w/index.php?title= Stat841&pr intable= yes 13/74 10/09/2013 Stat841 - Wiki Cour se Notes c a s f can also lsiy be used with other discriminant analysis algorithms. The steps laid out above would only need to be modified slightly for those algorithms. Re call: An analys is of the function of p i c m in matlab. rnop In our assignment 1, we have learnt that how to perform Principal Component Analysis using SVD method. In fact, the matlab offers us...
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## This document was uploaded on 03/07/2014.

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