PCA.h File Reference

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Classes
class	CPCA
	Preprocessor PCA performs principial component analysis on input feature vectors/matrices. When the init method in PCA is called with proper feature matrix X (with say N number of vectors and D feature dimension), a transformation matrix is computed and stored internally. This transformation matrix is then used to transform all D-dimensional feature vectors or feature matrices (with D feature dimensions) supplied via apply_to_feature_matrix or apply_to_feature_vector methods. This tranformation outputs the T-Dimensional approximation of all these input vectors and matrices (where T<=min(D,N)). The transformation matrix is essentially a DxT matrix, the columns of which correspond to the eigenvectors of the covariance matrix(XX') having top T eigenvalues. More...

Enumerations
enum	EPCAMethod { AUTO = 10, SVD = 20, EVD = 30 }
enum	EPCAMode { THRESHOLD, VARIANCE_EXPLAINED, FIXED_NUMBER }
enum	EPCAMemoryMode { MEM_REALLOCATE, MEM_IN_PLACE }