📄 matlab central - file detail - partial least-squares and discriminant analysis.mht
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<H1>Partial Least-Squares and Discriminant Analysis</H1>
<P id=3Dauthor>by <A=20
=
href=3D"http://www.mathworks.com/matlabcentral/fileexchange/authors/22524=
">Yi=20
Cao</A></P>
<P id=3Dsubmissiondate> </P>
<P>15 Feb 2008 (Updated 19 Feb 2008) </P>
<P id=3Dsummary>A tutorial and tool using PLS for discriminant =
analysis.</P>
<P id=3Dcollaboration><A class=3D"info notext"=20
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false;"=20
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ation">I=20
am interested in collaboration</A> </P>
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ing=3D18760">Watch=20
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<TR class=3Dtitle>
<TH colSpan=3D2><SPAN class=3Dheading>File =
Information</SPAN></TH></TR>
<TR>
<TD class=3Dlabel>Description</TD>
<TD>
<P>Patial Least-Squares (PLS) is a widely used technique in =
various=20
areas. This package provides a function to perform the PLS=20
regression using the Nonlinear Iterative Partial =
Least-Squares=20
(NIPALS) algorithm. It consists of a tutorial function to =
explain=20
the NIPALS algorithm and the way to perform discriminant =
analysis=20
using the PLS function. <BR> <BR>The difference =
between=20
the total least squares regression and partial least squares =
regression can be explained as follows: =
<BR> <BR>For=20
given independent data X and dependent data Y, to fit a =
model=20
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