PCA

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(Reducing the Data Dimension)
(Recovering an Approximation of the Data)
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Now, <math>\textstyle \tilde{x} \in \Re^k</math> is a lower-dimensional, "compressed" representation
Now, <math>\textstyle \tilde{x} \in \Re^k</math> is a lower-dimensional, "compressed" representation
of the original <math>\textstyle x \in \Re^n</math>.  Given <math>\textstyle \tilde{x}</math>, how can we recover an approximation <math>\textstyle \hat{x}</math> to  
of the original <math>\textstyle x \in \Re^n</math>.  Given <math>\textstyle \tilde{x}</math>, how can we recover an approximation <math>\textstyle \hat{x}</math> to  
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the original value of <math>\textstyle x</math>?  From the [[#Rotating the Data|previous section]], we know that <math>\textstyle x = U x_{\rm rot}</math>.  Further,  
+
the original value of <math>\textstyle x</math>?  From an [[#Rotating the Data|earlier section]], we know that <math>\textstyle x = U x_{\rm rot}</math>.  Further,  
we can think of <math>\textstyle \tilde{x}</math> as an approximation to <math>\textstyle x_{\rm rot}</math>, where we have
we can think of <math>\textstyle \tilde{x}</math> as an approximation to <math>\textstyle x_{\rm rot}</math>, where we have
set the last <math>\textstyle n-k</math> components to zeros.  Thus, given <math>\textstyle \tilde{x} \in \Re^k</math>, we can  
set the last <math>\textstyle n-k</math> components to zeros.  Thus, given <math>\textstyle \tilde{x} \in \Re^k</math>, we can  

Revision as of 23:18, 29 April 2011

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