The second principal component is with variance We need to maximize this variance subject to the normalizing constraint a’ 2 a 2 = 1 and the orthogonality constraint w’ 1 w 2 = 0. Show that the...


The second principal component is


with variance


We need to maximize this variance subject to the normalizing constraint a’2a2
= 1 and the orthogonality constraint w’1w2
= 0. Show that the orthogonality constraint is equivalent to a’1a2
= 0. Then, using two Lagrange multipliers, one for the normalizing constraint and the other for the orthogonality constraint, show that a2
is an eigenvector corresponding to the second-largest eigenvalue of RXX
. Explain how this procedure can be extended to derive the remaining k ' 2 principal components.



May 05, 2022
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