how to use princomp function
in [Matlab]
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From: Rupika Bandara on 17 Jun 2010 00:16 Hi all, I want to reduce dimensions of the data, therefore I need to use princomp function in MATLAB. Can I use (1x39) matrix as input to princomp function? When I use it I can get (39x39) matrix which comprises of 0 and 1. Can you please help me? Thank you
From: Steven Lord on 17 Jun 2010 09:57 "Rupika Bandara" <rupika23(a)yahoo.com> wrote in message news:hvc7i3$sui$1(a)fred.mathworks.com... > Hi all, > I want to reduce dimensions of the data, therefore I need to use princomp > function in MATLAB. Can I use (1x39) matrix as input to princomp function? Sure, although trying to generate principal components for 39 variables with just one lone observation sounds a bit sketchy to me. Normally wouldn't you want a LOT more data for such an analysis? -- Steve Lord slord(a)mathworks.com comp.soft-sys.matlab (CSSM) FAQ: http://matlabwiki.mathworks.com/MATLAB_FAQ To contact Technical Support use the Contact Us link on http://www.mathworks.com
From: Javier Montoya on 13 Jul 2010 05:28 On Jun 17, 3:57 pm, "Steven Lord" <sl...(a)mathworks.com> wrote: > "Rupika Bandara" <rupik...(a)yahoo.com> wrote in message > > news:hvc7i3$sui$1(a)fred.mathworks.com... > > > Hi all, > > I want to reduce dimensions of the data, therefore I need to use princomp > > function in MATLAB. Can I use (1x39) matrix as input to princomp function? > > Sure, although trying to generate principal components for 39 variables with > just one lone observation sounds a bit sketchy to me. Normally wouldn't you > want a LOT more data for such an analysis? Hi guys, Just to understand the input for princomp(X). From the 'help', it's written that the input X is a N-by-P data matrix X. This means, that the we have 'N' feature vectors, each containing 'P' elements, right? As an example, in my case I have a 27 feature vectors, each of 500 dimensionality (size(X) = 27x500). When I do: [COEFF, SCORE] = princomp(X) is turns out that in SCORE I have some values from columns 1 to 26, then from columns 27 to 500 there are just zeros. Best wishes
From: Peter Perkins on 13 Jul 2010 10:47
On 7/13/2010 5:28 AM, Javier Montoya wrote: > As an example, in my case I have a 27 feature vectors, each of 500 > dimensionality (size(X) = 27x500). When I do: > [COEFF, SCORE] = princomp(X) is turns out that in SCORE I have some > values from columns 1 to 26, then from columns 27 > to 500 there are just zeros. That is exactly what you should expect. With only 27 observations, the data can be rotated so that it lies in a 26 dim subspace of R^500. 26, because the column means are removed. If you don't want to see those, use the 'econ' flag. |