I'm currently struggling with PCA and Matlab. Let's say we have a data matrix X and a response y (classification task). X consists of 12 rows and 4 columns. The rows are the data points, the columns are the predictors (features).
Now, I can do PCA with the following command:
As I understood from the matlab documentation, coeff contains the loadings and score contains the principal components in the columns. That mean first column of score contains the first principal component (associated with the highest variance) and the first column of coeff contains the loadings for the first principal component.
Is this correct?
But if this is correct, why is then X * coeff not equal to score?