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| author | Daniel Wolff |
|---|---|
| date | Fri, 19 Aug 2016 13:07:06 +0200 |
| parents | |
| children |
| rev | line source |
|---|---|
| Daniel@0 | 1 <html> |
| Daniel@0 | 2 <head> |
| Daniel@0 | 3 <title> |
| Daniel@0 | 4 Netlab Reference Manual ppca |
| Daniel@0 | 5 </title> |
| Daniel@0 | 6 </head> |
| Daniel@0 | 7 <body> |
| Daniel@0 | 8 <H1> ppca |
| Daniel@0 | 9 </H1> |
| Daniel@0 | 10 <h2> |
| Daniel@0 | 11 Purpose |
| Daniel@0 | 12 </h2> |
| Daniel@0 | 13 Probabilistic Principal Components Analysis |
| Daniel@0 | 14 |
| Daniel@0 | 15 <p><h2> |
| Daniel@0 | 16 Synopsis |
| Daniel@0 | 17 </h2> |
| Daniel@0 | 18 <PRE> |
| Daniel@0 | 19 [var, U, lambda] = pca(x, ppca_dim) |
| Daniel@0 | 20 </PRE> |
| Daniel@0 | 21 |
| Daniel@0 | 22 |
| Daniel@0 | 23 <p><h2> |
| Daniel@0 | 24 Description |
| Daniel@0 | 25 </h2> |
| Daniel@0 | 26 |
| Daniel@0 | 27 <CODE>[var, U, lambda] = ppca(x, ppca_dim)</CODE> computes the principal component |
| Daniel@0 | 28 subspace <CODE>U</CODE> of dimension <CODE>ppca_dim</CODE> using a centred |
| Daniel@0 | 29 covariance matrix <CODE>x</CODE>. The variable <CODE>var</CODE> contains |
| Daniel@0 | 30 the off-subspace variance (which is assumed to be spherical), while the |
| Daniel@0 | 31 vector <CODE>lambda</CODE> contains the variances of each of the principal |
| Daniel@0 | 32 components. This is computed using the eigenvalue and eigenvector |
| Daniel@0 | 33 decomposition of <CODE>x</CODE>. |
| Daniel@0 | 34 |
| Daniel@0 | 35 <p><h2> |
| Daniel@0 | 36 See Also |
| Daniel@0 | 37 </h2> |
| Daniel@0 | 38 <CODE><a href="eigdec.htm">eigdec</a></CODE>, <CODE><a href="pca.htm">pca</a></CODE><hr> |
| Daniel@0 | 39 <b>Pages:</b> |
| Daniel@0 | 40 <a href="index.htm">Index</a> |
| Daniel@0 | 41 <hr> |
| Daniel@0 | 42 <p>Copyright (c) Ian T Nabney (1996-9) |
| Daniel@0 | 43 |
| Daniel@0 | 44 |
| Daniel@0 | 45 </body> |
| Daniel@0 | 46 </html> |