tensorly.decomposition.CPPower

class CPPower(rank, n_repeat=10, n_iteration=10, verbose=0)[source]

CP Decomposition via Robust Tensor Power Iteration

Parameters:	tensortl.tensor input tensor to decompose rankint rank of the decomposition (number of rank-1 components) n_repeatint, default is 10 number of initializations to be tried n_iterationint, default is 10 number of power iterations verbosebool level of verbosity
Returns:	(weights, factors) weights1-D tl.tensor of length rank contains the eigenvalue of each eigenvector factorslist of 2-D tl.tensor of shape (size, rank) Each column of each factor corresponds to one eigenvector

fit_transform(tensor)[source]

Decompose an input tensor

Parameters:	tensortensorly tensor input tensor to decompose
Returns:	CPTensor decomposed tensor