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Aug 27

principal component analysis

Posted by abiao at 17:06 | Code » Matlab | Comments(0) | Reads(11037)
Principal component analysis (PCA) is widely used for data research, for instance, interest rate analysis, VaR calculation of porfolio, etc. What is PCA? It is a method of discovering patterns in data, and conveying the data in such a manner to spotlight their similarities and divergences. Because patterns in data can be difficult to detect in data of high dimension, where the luxury of graphical representation is not available, PCA is a potent tool for analysing data.

The additional major benefit of PCA is that after you have obtained these patterns in the data, and you compact the data, ie. by reducing the number of dimensions, without much loss of information.

wiki(principal component analysis)

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