pca()
Description:
External library function; 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
Parameters:
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A |
A matrix |
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n |
Number of principal components |
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F |
The PCA fiiting object returned by pca(A,n) |
Options:
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@r |
Enable returning the result of demenionality reduction on matrix A, which is a matrix of n columns, directly |
Return value:
A PCA fitting object or a sequence
Example:
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A |
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1 |
[[1,2,3,4],[2,3,1,2],[1,1,1,-1],[1,0,-2,-6]] |
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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
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3 |
=pca(A1,A2) |
Execute dimensionality reduction on A1
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4 |
=pca@r(A1,2) |
Use @r option to reduce A1’s dimensionality directly; result is the same as A3’s |
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5 |
[[4,6,2,4],[2,3,1,2],[1,1,1,-1]] |
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6 |
=pca(A5,A2) |
Exectue dimensionality reduction on another matrix having same number of columns as the original matrix
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