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Which of the following correctly describes the sequence and purpose of steps in Linear Discriminant Analysis (LDA)?
Compute class means → compute overall mean → compute within-class scatter → compute between-class scatter → solve generalized eigenvalue problem → sort eigenvalues → form projection matrix → project data.
Compute eigenvectors first → compute class means → compute overall mean → form projection matrix → compute scatter matrices → project data → sort eigenvalues.
Compute the overall mean → compute class means → compute within-class scatter → compute between-class scatter → solve generalized eigenvalue problem → sort eigenvalues → form projection matrix → project data.
Compute within-class scatter → compute between-class scatter → compute class means → compute overall mean → solve eigenvalue problem → sort eigenvalues → project data → form projection matrix.
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