Re: Principal Components
- To: mathgroup at smc.vnet.net
- Subject: [mg131880] Re: Principal Components
- From: Bob Hanlon <hanlonr357 at gmail.com>
- Date: Wed, 23 Oct 2013 23:44:14 -0400 (EDT)
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- Delivered-to: l-mathgroup@wolfram.com
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- References: <20131022044958.08F3C6A23@smc.vnet.net>
Covariance is the default method
$Version
"9.0 for Mac OS X x86 (64-bit) (January 24, 2013)"
Options[PrincipalComponents]
{Method -> "Covariance"}
mat = {{1., 2}, {2, 3}, {4, 10}};
pc1 = PrincipalComponents[mat]
{{3.27053, 0.285293}, {1.99969, -0.335165}, {-5.27023, 0.0498715}}
pc1 == PrincipalComponents[mat,
Method -> "Covariance"] ==
PrincipalComponents[pc1] ==
PrincipalComponents[pc1,
Method -> "Covariance"]
True
pc2 = PrincipalComponents[mat,
Method -> "Correlation"]
{{1.10388, 0.130549}, {0.478746, -0.170139}, {-1.58262, 0.0395904}}
pc2 == PrincipalComponents[pc2] ==
PrincipalComponents[pc2,
Method -> "Covariance"]
True
Bob Hanlon
On Tue, Oct 22, 2013 at 12:49 AM, pw <p.willis at telus.net> wrote:
>
> Hello,
>
> The function 'PrincipalComponents' returns the the first principal
> components vector of a group of input vectors.
>
> Question 1.) Is it possible to define Method->"covariance" or is
> correlation the only PC technique available?
>
> Question 2.) How can I generate an inverse PC transform from my
> PrincipalComponents output?
>
>
> Thanks,
>
>
> Peter
>
>
- References:
- Principal Components
- From: pw <p.willis@telus.net>
- Principal Components