MATLAB: PCA matrix data compression help

anndata compressionneural networkpcaprinciple component analysis

Hi,
I'm making a neural network for classification(newff or patternnet) and I have a input matrix 400×500 (rows x column) and a target vector 1×500 with [zeros ones] my true/false.
Which PCA algorithm and how I should use on my input matrix to get a matrix 100×500 or 10×500 or 5×500 (data compression) but also to use my target matrix with zeros&ones on this data?
Thank you 🙂

Best Answer

For classification, choose the dimensions in the direction of greatest class separation.
This is not guaranteed using PCA which chooses the dimensions with the largest variances.
For a detailed explanation, search comp.ai.neural-nets and/or comp.soft-sys.matlab with
heath cigar
heath parallel cigar
PLS (Partial-Least-Squares) is more appropriate.
Hope this helps.
Greg
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