Difference between revisions of "User talk:Joyce Whang"

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In this term project, I will make a lecture about Principal Component Analysis (PCA). PCA is one of the most widely used techniques for linear dimensionality reduction.
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In this term project, I will make a lecture about Principal Component Analysis (PCA). PCA is one of the most widely used techniques for linear dimensionality reduction. <br>
  
'''Motivation''' <br>
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'''1. Motivation''' <br>
 
- PCA is introduced to deal with the problem of excessive dimensionality. <br>
 
- PCA is introduced to deal with the problem of excessive dimensionality. <br>
 
- We can reduce a complex data set to a lower dimension by PCA. <br>
 
- We can reduce a complex data set to a lower dimension by PCA. <br>
 
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Revision as of 03:35, 9 April 2012

In this term project, I will make a lecture about Principal Component Analysis (PCA). PCA is one of the most widely used techniques for linear dimensionality reduction.

1. Motivation
- PCA is introduced to deal with the problem of excessive dimensionality.
- We can reduce a complex data set to a lower dimension by PCA.
-