Description:
External library function (See External Library Guide); perform PCA on a matrix and return data for dimensionality reduction.
Syntax:
pca(A,n) |
Perform PCA (Principal Component Analysis) on matrix A and return data for dimensionality reduction; n is the number of principal components |
pca(A,F) |
Reduce dimensionality for another matrix having same number of columns |
Parameter:
A |
A matrix |
n |
Number of principal components |
F |
The PCA fitting object returned by pca(A,n) |
Option:
@r |
Enable returning the result of dimensionality reduction on matrix A, which is a matrix of n columns, directly |
Return value:
A PCA fitting object or a sequence
Example:
|
A |
|
1 |
[[1,2,3,4],[2,3,1,2],[1,1,1,-1],[1,0,-2,-6]] |
|
2 |
=pca(A1,2) |
Return data for dimensionality reduction: A2(1) Averages of columns; A2(2) Variances of principal components ordered descendingly. A2(3) Coefficients of principal components. |
3 |
=pca(A1,A2) |
Execute dimensionality reduction on A1. |
4 |
=pca@r(A1,2) |
Use @r option to reduce A1’s dimensionality directly; result is the same as A3’s. |
5 |
[[4,6,2,4],[2,3,1,2],[1,1,1,-1]] |
|
6 |
=pca(A5,A2) |
Execute dimensionality reduction on another matrix having same number of columns as the original matrix. |