Table of Symbols and Abbreviations
| Symbol | Meaning | Dimensions | Indices |
|---|---|---|---|
| data matrix, consisting of the set of all data vectors, one vector per column | |||
| the number of column vectors in the data set | scalar | ||
| the number of elements in each column vector (dimension) | scalar | ||
| the number of dimensions in the dimensionally reduced subspace, | scalar | ||
| vector of empirical means, one mean for each row m of the data matrix | |||
| vector of empirical standard deviations, one standard deviation for each row m of the data matrix | |||
| vector of all 1's | |||
| deviations from the mean of each row m of the data matrix | |||
| z-scores, computed using the mean and standard deviation for each row m of the data matrix | |||
| covariance matrix | |||
| correlation matrix | |||
| matrix consisting of the set of all eigenvectors of C, one eigenvector per column | |||
| diagonal matrix consisting of the set of all eigenvalues of C along its principal diagonal, and 0 for all other elements | |||
| matrix of basis vectors, one vector per column, where each basis vector is one of the eigenvectors of C, and where the vectors in W are a sub-set of those in V | |||
| matrix consisting of N column vectors, where each vector is the projection of the corresponding data vector from matrix X onto the basis vectors contained in the columns of matrix W. |
Read more about this topic: Principal Component Analysis
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