Principal Component Analysis

Different parts of a vehicle

What is PCA?

Principal component algorithm finding the direction of maximum variance

Statistical interpretation

x¯=∑i=1nxi

x¯ = [1,1,1,1] * [x¯]

M = x¯ — x¯

M = X (data matrix ) — X (mean of the rows)

K = M(Transpose) *M

therefore K = FG.

T = M * F

In a nutshell, this whole process explained above is meant to decompose a matrix in the direction of maximum variance in order to capture the most important features of a given data matrix.

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