TikhonovSolverDecoupled

class TikhonovSolverDecoupled(regularizer, method='svd')

Solve r independent l2-norm ordinary least-squares problems, each with the same data matrix but a different Tikhonov regularizer,

min_{x_i} ||Ax_i - b_i||_2^2 + ||P_i x_i||_2^2, i = 1, …, r.

Properties

A	Left-hand side data matrix.
B	"Right-hand side matrix B = [ b_1 | .
d	Number of unknowns to learn in each problem (number of columns of A).
k	Number of equations in the least-squares problem (number of rows of A).
method	Strategy for solving the regularized least-squares problem.
r	Number of independent least-squares problems (number of columns of B).
regularizer	Symmetric semi-positive-definite regularization matrices [P_1, ..., P_r], one for each column of X and B (r (d, d) ndarrays)

Methods

cond	Calculate the 2-norm condition number of the data matrix A.
fit	Store A and B.
misfit	Calculate the data misfit (residual) of the non-regularized problem for each column of B = [ b_1 | .
predict	Solve the least-squares problems.
regcond	Compute the 2-norm condition number of each regularized data matrix.
residual	Calculate the residual of the regularized problem for each column of B = [ b_1 | .